RRIdesign.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9515d115-170a-4951-ba38-b9d6819c12b2",
   "metadata": {},
   "source": [
    "# Sequence design for RNA-RNA interactions\n",
    "\n",
    "The design of RNA sequences with desired structural properties presents\n",
    "a challenging computational problem with promising applications in biotechnology\n",
    "and biomedicine. Most regulatory RNAs function by forming RNA-RNA interactions,\n",
    "e.g., in order to regulate mRNA expression. It is therefore natural to consider\n",
    "problems where a sequence is designed to form a desired RNA-RNA interaction and\n",
    "switch between structures upon binding. This contribution demonstrates the use of\n",
    "the Infrared framework to design interacting sequences. Specifically, we consider\n",
    "the regulation of the rpoS mRNA by the sRNA DsrA and design artificial 5’UTRs\n",
    "that place a downstream protein coding gene under control of DsrA."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a56ae977-512b-4147-9cc7-4512d91d41e3",
   "metadata": {},
   "source": [
    "### Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bbc53cc2-9d2e-4c42-b6d4-b80d5550733f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "import math\n",
    "from PIL import Image\n",
    "import time\n",
    "\n",
    "# Third party package\n",
    "import RNA\n",
    "import infrared\n",
    "## We need to implicit import infrared.rna for version <= 1.2\n",
    "import infrared.rna\n",
    "## Script for this project\n",
    "import rri"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91e0d731-0088-4749-b7ba-018acb81f90c",
   "metadata": {},
   "source": [
    "# The DsrA-rpoS regulation example\n",
    "The sRNA DsrA is known to regulating the translation of RpoS by binding to the 5'UTR of rpoS mRNA and therby inducing a change in the mRNA structure, making the ribosome binding side(RBS) accessible."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06744724-a67b-4f57-82a4-cca65171f993",
   "metadata": {},
   "source": [
    "## Native DsrA structure \n",
    "\n",
    "DsrA on its addopts a conformation with three stem-loop (SL) structures. The first(SL1) and (SL3) are predicted and experimentally confirmed to be stable and unique while the region of the SL2 is thought to have multiple alternative folds. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bc96b4ab-6d45-4be4-aa3a-6d50309c0fc5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# DsrA from e.coli; NC_000913.3(2025313-2025225)\n",
    "dsra_seq     = \"AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU\"\n",
    "dsra_str     = '...(((((((.....)))))))...(((((((((((((.......))))))).)))))).((((((((((.....))))))))))....'\n",
    "dsra_str_alt = \"...(((((((.....)))))))....................(((((....)))))....((((((((((.....))))))))))....\"\n",
    "dsra_str_min = '...(((((((.....)))))))......................................((((((((((.....))))))))))....'\n",
    "dsra_inter   = \".........((((((((..(((((((((((((..((((((.................................................\"\n",
    "dsra_len = len(dsra_seq)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "458415d6-d3fd-4436-a8d5-425b0eb7b0a3",
   "metadata": {},
   "source": [
    "## Native rpoS structure \n",
    "The rpoS mRNA is poorly transcribed, since the ribosome binding site is sequestered in a stable secondary structure. We define the ribosome binding site as a 30nt region starting at the Shine-Dalgarno motif (AGGAGC in the rpoS mRNA).\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d1d45c6d-6c19-4cf4-aa2c-57e08e415b3e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'SD': 'AGGAGC', 'SD_pos': 139, 'AUG_pos': 151, 'BP_SPAN': 200}\n"
     ]
    }
   ],
   "source": [
    "# rpoS 5'UTR fragment (TSS -150nts +27nts):  NC_000913.3(2867701-2867525)\n",
    "             #....,....1....,....2....,....3....,....4....,....5....,....6....,....7....,....8....,....9....,....0....,....1....,....2....,....3....,....4....,....5....,....6....,....7....,....8....,....9....,....0\n",
    "             #NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNaggagcNNNNNNaugagNNNNNNNNNNNNNNNNNNNNNN\n",
    "rpos_seq =   \"CACCGGAACCAGUUCAACACGCUUGCAUUUUGAAAUUCGUUACAAGGGGAAAUCCGUAAACCCGCUGCGUUAUUUGCCGCAGCGAUAAAUCGGCGGAACCAGGCUUUUGCUUGAAUGUUCCGUCAAGGGAUCACGGGUAGGAGCCACCUUAUGAGUCAGAAUACGCUGAAAGUUCAU\"\n",
    "rpoS_inter = \"........................)))))).)))))))))))))..))))))))...........................................................................................................................\"\n",
    "rpos_str   = \"...................................(((((...((((((..((((((...(((...............................................................)))...)))))).....)).)))))))))......................\"\n",
    "rpos_len = len(rpos_seq)\n",
    "\n",
    "# set some rpos specific parameters\n",
    "rri.PARAMS['SD_pos'] = rpos_seq.find(rri.PARAMS['SD'])+1  # ViennaRNA uses 1-based coords\n",
    "rri.PARAMS['AUG_pos'] = rpos_seq.find('AUGAG')+1\n",
    "\n",
    "# set some structure prediction parameters\n",
    "## setting the maximum base pair span at least ~20nts below the mRNA length avoids artifacts\n",
    "## originating from the fact that the 3' end of mRNA fragment is not the actual end of the RNA sequence\n",
    "rri.PARAMS['BP_SPAN'] = 200\n",
    "\n",
    "print(rri.PARAMS)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc89c598-b0f2-4875-92bb-3c8b28b2e22a",
   "metadata": {},
   "source": [
    "## Plots of the predicted mfe structure of DsrA and the rpoS 5'UTR before binding"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "28d72098-1499-4994-9955-3755533148dd",
   "metadata": {},
   "source": [
    "Predict secondary structures of undbound RNAs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fe888ace-c0cb-4315-9a54-7e728aec4248",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CACCGGAACCAGUUCAACACGCUUGCAUUUUGAAAUUCGUUACAAGGGGAAAUCCGUAAACCCGCUGCGUUAUUUGCCGCAGCGAUAAAUCGGCGGAACCAGGCUUUUGCUUGAAUGUUCCGUCAAGGGAUCACGGGUAGGAGCCACCUUAUGAGUCAGAAUACGCUGAAAGUUCAU\n",
      ".....((((...((((....((....(((((((..(((((...((((((..((((((...(((((((((........))))))........(((((((((((((....)))))...))))))))..)))...)))))).....)).))))))))))))))))..)))))).))))..\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU\n",
      "...(((((((.....)))))))...(((((((((((((.......))))))).)))))).((((((((((.....))))))))))....\n"
     ]
    }
   ],
   "source": [
    "# UnBound\n",
    "rpos_unbound, dsra_unbound = rri.prediction_unbound(rpos_seq, dsra_seq)\n",
    "print(rpos_seq)\n",
    "print(rpos_unbound)\n",
    "print(dsra_seq)\n",
    "print(dsra_unbound)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d41d03f4-bca1-4bee-a3a0-cef2cbe744fe",
   "metadata": {},
   "source": [
    "Get secondary structure plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cfc0cd00-e2c8-45fc-b9f8-90801a7e5293",
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<PIL.EpsImagePlugin.EpsImageFile image mode=RGB size=700x700>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from PIL import Image\n",
    "\n",
    "rri.draw_RNAplot(\n",
    "    dsra_seq,\n",
    "    rpos_seq,\n",
    "    dsra_unbound,\n",
    "    rpos_unbound,\n",
    "    SD_pos=rri.PARAMS[\"SD_pos\"],\n",
    "    SD_len=6,\n",
    "    AUG_pos=rri.PARAMS[\"AUG_pos\"],\n",
    "    output=\"unbound_DsrA_rpoS.ps\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "416c5cbd-6e3b-41be-abcd-87ee2f50a1f4",
   "metadata": {},
   "source": [
    "## Accessibility of the RBS in the unbound rpoS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f82645f-0de8-4197-b589-b1d84eb449c6",
   "metadata": {},
   "source": [
    "Let's compute the opening energy of the ribosome binding withnout sRNA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "04a9c04f-9e49-4505-a41f-04a31fd236b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 11.23 kcal/mol\n"
     ]
    }
   ],
   "source": [
    "# Free-energy required to open the region of 30nts from Shine-Dalgarno motif at unbound rpos\n",
    "print('{:6.2f} kcal/mol'.format(rri.dGopen(rpos_seq, (rri.PARAMS['SD_pos'], rri.PARAMS['SD_pos']+29))))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "496da141-4e75-40bc-baef-14df143f8e74",
   "metadata": {},
   "source": [
    "## The DsrA - rpoS interaction \n",
    "Next, we compute the opening energy after binding of dsRNA\n",
    "\n",
    "To this end, we first predict the interaction using RNAup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8b3af590-9391-4b62-a990-73db422bc53e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Binding region of rpos: (25, 54)\n",
      "Binding region of rdsa: (10, 40)\n",
      "Binding Energy: -11.93 kcal/mol\n"
     ]
    }
   ],
   "source": [
    "# Bound region computed using RNAup and binding energy\n",
    "i, j, k, l, be = rri.RNAup(rpos_seq, dsra_seq)\n",
    "print(\"Binding region of rpos:\", (i, j))\n",
    "print(\"Binding region of rdsa:\", (k, l))\n",
    "print(\"Binding Energy:\", be, \"kcal/mol\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ad9b2c2-35a9-4354-bd5b-9e9384f6e37f",
   "metadata": {},
   "source": [
    "Next, we compute and drawing of the resulting DsrA-rpoS complex. For simplicity we do not show DsrA structure, except for the inter-molecular base pairs:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "590bfebe-4b0b-4220-99ec-6ebd2342ef89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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      "image/png": 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",
      "text/plain": [
       "<PIL.EpsImagePlugin.EpsImageFile image mode=RGB size=700x700>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bound\n",
    "rpos_bound, dsra_bound = rri.prediction_bound(rpos_seq, dsra_seq)\n",
    "rri.draw_RNAplot(dsra_seq, rpos_seq, dsra_bound, rpos_bound, output='bound_DsrA_rpoS.ps')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "430a57f9-0727-4e00-bb65-f04b58d2e146",
   "metadata": {},
   "source": [
    "We can also compute the energylandscape and kinetic features of the interaction with RRIkinDP (https://github.com/mwaldl/RRIkinDP/tree/dev)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d6df1a4a-db02-4856-95e7-a804e5f5086a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- free energy of the full interaction with RRIkinDP: -11.69kcal/mol\n",
      "- free energy of the barrier state: 0.68kcal/mol\n",
      "- free energy of 5bps seed from which the minimum barrier folding paths starts: 0.68kcal/mol\n",
      "- seed resulting in the minimum barrier state folding path starts at base pair 12\n",
      "The interaction range on the sRNA is 10-40\n",
      "The interaction range on the mRNA is 25-54\n",
      "Base pair list: (10,54):(11,53):(12,52):(13,51):(14,50):(15,49):(16,48):(17,47):(20,44):(21,43):(22,42):(23,41):(24,40):(25,39):(26,38):(27,37):(28,36):(29,35):(30,34):(31,33):(32,32):(35,30):(36,29):(37,28):(38,27):(39,26):(40,25)\n",
      "interaction in db notation: .........((((((((..(((((((((((((..((((((.................................................&........................)))))).)))))))))))))..))))))))...........................................................................................................................\n",
      "E: -11.39, ED1: 9.22, ED2: 12.09, E_loops: -34.9\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rri.plot_energylandscape(dsra_seq, rpos_seq, id1='DsrA', id2=\"rpoS 5'UTR\", figure_path=\"natural_kinetic_landscape.pdf\", verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81f2520e-0c84-40b7-8fc0-25cc06554b8d",
   "metadata": {},
   "source": [
    "## Accessibility of the RBS in the bound rpoS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c086631e-43cc-4b6f-abbb-cd9d2f2462ae",
   "metadata": {},
   "source": [
    "Plus next we calculate the RBS opening energy under the constraint that the region bound by the sRNA cannot form intra-molecular interactions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4209a60f-37a7-4eaf-ac8c-1c07d960bac8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  6.34 kcal/mol\n"
     ]
    }
   ],
   "source": [
    "# Free-energy required to open the region of 30nts from Shine-Dalgarno motif at bound rpos\n",
    "print('{:6.2f} kcal/mol'.format(rri.dGopen(rpos_seq, (rri.PARAMS['SD_pos'], rri.PARAMS['SD_pos']+29), constraint=(i, j))))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c465da6-7369-401d-8393-3598a098f533",
   "metadata": {},
   "source": [
    "# The design\n",
    "\n",
    "We're now ready to design novel mRNAs that are controlled by DsrA, similar to rpoS. First we need to setup the sequence and structure constraints.\n",
    "\n",
    "\n",
    "### Sequence constraint\n",
    "In our example we assume GFP as the target protein. Below we enter the first exonsof GFP (GenBank: M62654.1  208 to 413) ) and select the first 9 codons (27 nts) as input coding sequence that follows after the designed 5'UTR:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4838db11-ca7a-496b-97f6-f34f898009b9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "length of input cds: 206\n",
      "sequence constraint based on the first 27nts of the targeted cds: AUGAGUAAAGGAGAAGAACUUUUCACU\n"
     ]
    }
   ],
   "source": [
    "gfp_cds = 'AUGAGUAAAGGAGAAGAACUUUUCACUGGAGUUGUCCCAAUUCUUGUUGAAUUAGAUGGUGAUGUUAAUGGGCACAAAUUCUCUGUCAGUGGAGAGGGUGAAGGUGAUGCAACAUACGGAAAACUUACCCUUAAAUUUAUUUGCACUACUGGAAAGCUACCUGUUCCAUGGCCAACACUUGUCACUACUUUCUCUUAUGGUGUUCA'\n",
    "print(f'length of input cds: {len(gfp_cds)}')\n",
    "\n",
    "len_cds_C = 27\n",
    "cds = gfp_cds[:len_cds_C]\n",
    "\n",
    "print(f'sequence constraint based on the first {len_cds_C}nts of the targeted cds: {cds}')\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a7ec4e2-23ca-456b-8b72-1611a71a1c9d",
   "metadata": {},
   "source": [
    "\n",
    "Following the DsrA-rpoS example, our designs consists of 150 nt upstream of the AUG start codon. We include the sequence (AGGAGC) and position of the rpoS Shine-Delarno motif. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "47d6e7a2-addc-4e28-8977-6c5918faac7c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "start of the SD motive: 138, SD motive: AGGAGC\n",
      "5'UTR constraint\n",
      "NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNAGGAGCNNNNNN\n"
     ]
    }
   ],
   "source": [
    "sd_pos = rri.PARAMS['SD_pos'] - 1\n",
    "sd_motif = rri.PARAMS['SD']\n",
    "print(f'start of the SD motive: {sd_pos}, SD motive: {sd_motif}')\n",
    "\n",
    "preAUG = ['N'] * 150\n",
    "preAUG[138:144] = 'AGGAGC'\n",
    "preAUG = ''.join(preAUG)\n",
    "print(\"5'UTR constraint\")\n",
    "print(preAUG)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ed6c0d5-33cd-4ada-aa7e-bb9ceb1b6c0e",
   "metadata": {},
   "source": [
    "To represent the full design we need to merge the fixed DsrA sequence, the 5'UTR and the start of the coding sequence:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b0dc4713-6a76-4607-8254-ff3c392f3039",
   "metadata": {},
   "outputs": [],
   "source": [
    "sequence_C  = dsra_seq + preAUG + cds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29f985a9-fc2d-41b9-b961-ca7168dfda4b",
   "metadata": {},
   "source": [
    "### Structure constraint\n",
    "\n",
    "Infrared can extract structure contraints from dot braket strings and enforces compatible nucleotides for pairing positions. Each sonstraint string has the length of the full design (DsrA + 150nts UTR + 27nts CDS). \n",
    "We set up constraints for the DsrA structure (sRNA_str_C), the helix in the rpoS UTR that makes the RBS unaccessible (mRNA_str_C) the interaction base pairs between DsrA and the rpoS UTR (inter_str_C)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "9e389bed-e569-4639-9fda-299dc790443d",
   "metadata": {},
   "outputs": [],
   "source": [
    "sRNA_str_C  = dsra_str_min + \".\" * (len(sequence_C) - dsra_len)\n",
    "mRNA_str_C  = '.' * dsra_len + rpos_str                   \n",
    "inter_str_C = dsra_inter + rpoS_inter"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8cfbaec9-7cff-4371-970b-effa33bb6c4d",
   "metadata": {},
   "source": [
    "### Print constraints"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "00f4b990-e011-4fd8-966e-62583d53dc15",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUUNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNAGGAGCNNNNNNAUGAGUAAAGGAGAAGAACUUUUCACU\n",
      "...(((((((.....)))))))......................................((((((((((.....)))))))))).....................................................................................................................................................................................\n",
      "............................................................................................................................(((((...((((((..((((((...(((...............................................................)))...)))))).....)).)))))))))......................\n",
      ".........((((((((..(((((((((((((..((((((.........................................................................)))))).)))))))))))))..))))))))...........................................................................................................................\n"
     ]
    }
   ],
   "source": [
    "print(sequence_C)\n",
    "print(sRNA_str_C)\n",
    "print(mRNA_str_C)\n",
    "print(inter_str_C)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9a467c6-9a16-4b26-a0ce-6844b605c588",
   "metadata": {},
   "source": [
    "## Infrared model\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5fc46567-ec24-4cd8-9562-1600829cb461",
   "metadata": {},
   "outputs": [],
   "source": [
    "# RRI general Model factory\n",
    "def design_model(seq_IUPAC, sRNA_str, mRNA_str, inter_str, split_rna):\n",
    "    \"\"\"Infrared model factory for general RRI project\n",
    "\n",
    "    Args:\n",
    "        seq_IUPAC: sequence constraints in IUPAC format. The sequence is the concatenation of small RNA and mRNA sequences, e.g. dsra+rpos\n",
    "        sRNA_str: structure constraints for the sRNA\n",
    "        mRNA_str: structure constraints for the mRNA\n",
    "        inter_str: structure constraints for the for the interaction region\n",
    "        split_rna: function to split sequence into sRNA and mRNA\n",
    "    \"\"\"\n",
    "    # Initial model with sequence length and alphabet size\n",
    "    n = len(seq_IUPAC)\n",
    "    model = infrared.Model(n, 4)\n",
    "    # Set each variable domain w.r.t given sequence constraint\n",
    "    for i, x in enumerate(seq_IUPAC):\n",
    "        model.add_constraints(infrared.ValueIn(i, infrared.rna.iupacvalues(x.upper())))\n",
    "\n",
    "    # function for controlling GC content, negative weight to avoid too high GC\n",
    "    # model.add_functions([infrared.rna.GCCont(i) for i in subset], 'gc')\n",
    "    # model.set_feature_weight(-0.3, 'gc')\n",
    "\n",
    "    # Add structure constraint and Basepair energy\n",
    "    for name, ss in [(\"S\", sRNA_str), (\"M\", mRNA_str), (\"I\", inter_str)]:\n",
    "        bps = infrared.rna.parse(ss)\n",
    "        model.add_constraints(infrared.rna.BPComp(i, j) for (i, j) in bps)\n",
    "        model.add_functions(\n",
    "            [infrared.rna.BPEnergy(i, j, (i - 1, j + 1) not in bps) for (i, j) in bps],\n",
    "            f\"energy{name}\",\n",
    "        )\n",
    "        # If one wants to control initial sequence energy\n",
    "        model.add_feature(\n",
    "            f\"Energy{name}\",\n",
    "            f\"energy{name}\",\n",
    "            lambda sample, ss=ss: RNA.energy_of_struct(\n",
    "                infrared.rna.ass_to_seq(sample), ss\n",
    "            ),\n",
    "        )\n",
    "\n",
    "    # Trick to get positions that should be considered to resample during optimization\n",
    "    fixed = [i for i in range(n) if seq_IUPAC[i].upper() in \"ACGU\"]\n",
    "    # Get all connected components\n",
    "    ccs = model.connected_components()\n",
    "    # Keep cc if any of variable value is not fixed\n",
    "    model.my_connected_components = [\n",
    "        cc for cc in ccs if any(x not in fixed for x in cc)\n",
    "    ]\n",
    "    model.input_str = {\"sRNA\": sRNA_str, \"mRNA\": mRNA_str, \"inter\": inter_str}\n",
    "    model.ass_to_rna = lambda t: split_rna(infrared.rna.ass_to_seq(t))\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "faf19421-e8e7-48a1-b6ae-5c9ca1c6e5f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_rri = design_model(sequence_C, sRNA_str_C, mRNA_str_C, inter_str_C, lambda t: (t[:dsra_len], t[dsra_len:]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d2bea3b-bf8e-4ffd-8a0f-d2c0f8a56162",
   "metadata": {},
   "source": [
    "## Optimizations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "68b04456-befb-465d-a6ff-3fa16e75f0e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Optimizer with simple resampling adapted from Infrared Bookchapter\n",
    "def mc_optimize(model, cost, steps=1000, temp=0.01, sample=None, verbose=False):\n",
    "    sampler = infrared.Sampler(model)\n",
    "\n",
    "    cur = sampler.sample() if sample is None else sample()\n",
    "    curval = cost(*model.ass_to_rna(cur), verbose=False)\n",
    "\n",
    "    best, bestval = cur, curval\n",
    "    if verbose:\n",
    "        print(model.ass_to_rna(best)[1], bestval)\n",
    "    cur_step = 0\n",
    "    while cur_step < steps:\n",
    "        # In a more complicate case, one should sample cc with weight as cc size\n",
    "        # but we can ignore in here as all cc sizes are small\n",
    "        cc = random.choice(model.my_connected_components)\n",
    "        new = sampler.resample(cc, cur)\n",
    "        # resample till new assignment is different\n",
    "        while new.values() == cur.values():\n",
    "            cc = random.choice(model.my_connected_components)\n",
    "            new = sampler.resample(cc, cur)\n",
    "        cur_step += 1\n",
    "        newval = cost(*model.ass_to_rna(new), verbose=False)\n",
    "        # print(*model.ass_to_rna(cur), curval)\n",
    "        if newval - curval > 50 * temp:\n",
    "            continue\n",
    "        # print(infrared.rna.ass_to_seq(cur), curval, newval-curval, temp)\n",
    "        if newval <= curval or random.random() <= math.exp((curval - newval) / temp):\n",
    "            cur, curval = new, newval\n",
    "            if curval < bestval:\n",
    "                best, bestval = cur, curval\n",
    "                if verbose:\n",
    "                    print(model.ass_to_rna(best)[1], bestval)\n",
    "    return (best, bestval)\n",
    "\n",
    "\n",
    "# Simulated annealing instead of constant temperature MC\n",
    "def sa_optimize(model, cost, steps=500, temp=1, t_min=1e-6, sample=None, verbose=False):\n",
    "    assert temp >= t_min\n",
    "    cool = math.pow(t_min / temp, 1 / steps)\n",
    "    sampler = infrared.Sampler(model)\n",
    "\n",
    "    cur = sampler.sample() if sample is None else sample()\n",
    "    curval = cost(*model.ass_to_rna(cur), verbose=False)\n",
    "\n",
    "    best, bestval = cur, curval\n",
    "    if verbose:\n",
    "        print(*model.ass_to_rna(best), bestval)\n",
    "    cur_step = 0\n",
    "    while cur_step < steps:\n",
    "        cc = random.choice(model.my_connected_components)\n",
    "        new = sampler.resample(cc, cur)\n",
    "        # resample till new assignment is different\n",
    "        while new.values() == cur.values():\n",
    "            cc = random.choice(model.my_connected_components)\n",
    "            new = sampler.resample(cc, cur)\n",
    "        cur_step += 1\n",
    "        newval = cost(*model.ass_to_rna(new), verbose=verbose)\n",
    "        if newval - curval > 50 * temp:\n",
    "            continue\n",
    "        # print(infrared.rna.ass_to_seq(cur), curval, newval-curval, temp)\n",
    "        if newval <= curval or random.random() <= math.exp((curval - newval) / temp):\n",
    "            cur, curval = new, newval\n",
    "            if curval < bestval:\n",
    "                best, bestval = cur, curval\n",
    "                if verbose:\n",
    "                    print(*model.ass_to_rna(best), bestval)\n",
    "        # temp = max(temp * cool, 1e-6)\n",
    "    return (best, bestval)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "81e36d28-5bf6-4a60-9999-007320ffa910",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Multiple optimization runs for RRI design\n",
    "# With option of targeted sampling\n",
    "def run_optimize(\n",
    "    run, model, cost, optimize=sa_optimize, EI=-30, EM=-15, verbose=False, **kwargs\n",
    "):\n",
    "    \"\"\"Multiple calls of optimize\n",
    "\n",
    "    Args:\n",
    "        run (int): number of calls\n",
    "        model: infrared model (should contain member variable my_connected_components, see design_model_basic)\n",
    "        cost: cost function\n",
    "        EI: target energy for interaction region of seed sequence\n",
    "        ER: target energy for rpos structure of seed sequence\n",
    "        verbose (bool): enable verbose mode\n",
    "        kwargs: keyword arguments passed to optimization\n",
    "    \"\"\"\n",
    "    sampler = infrared.Sampler(model)\n",
    "    sample = sampler.sample\n",
    "    if EI is not None:\n",
    "        sampler.set_target(EI, 4, \"EnergyI\")\n",
    "        sample = sampler.targeted_sample\n",
    "    if EM is not None:\n",
    "        sampler.set_target(EM, 4, \"EnergyM\")\n",
    "        sample = sampler.targeted_sample\n",
    "    for ind in range(run):\n",
    "        best, bestval = optimize(model, cost, sample=sample, verbose=verbose, **kwargs)\n",
    "        sRNA, mRNA = model.ass_to_rna(best)\n",
    "    return sRNA, mRNA, bestval\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0ce4c57-02eb-48ed-95da-daa2c1c3a8e5",
   "metadata": {},
   "source": [
    "## Thermodynamic cost function\n",
    "\n",
    "Here is a first cost function. Our function consists of 4 terms:\n",
    "- The free energy of binding between sRNA and mRNA (preAUG region)\n",
    "- The RBS opening energy, with and without sRNA\n",
    "- The difference between the two openening energies\n",
    "\n",
    "In order to ensure that the optimization procedure will optimize **all** terms, rather than focusing only on the easiest aspect, we define a target value for each term and use a `LogSumExp` (LSE) as a smooth maximimum function.\n",
    "This ensures that, if one of the terms becomes significantly better than the target value, further opimizing this term has negligible effect on the overall cost.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "587bda68-4898-459f-9e15-4e5f172c060e",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.93  11.23   6.34 \t normalized + weighted:   0.21   0.35   0.07   0.70\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "1.748843133352433"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "def LogSumExp(*xs):\n",
    "    c = max(xs)\n",
    "    sum = 0\n",
    "    for x in xs:\n",
    "        sum = sum + math.exp(x - c)\n",
    "    return c + math.log(sum)\n",
    "\n",
    "\n",
    "def cost_dG(\n",
    "    sRNA,\n",
    "    mRNA,\n",
    "    region=(rri.PARAMS[\"SD_pos\"], rri.PARAMS[\"SD_pos\"] + 29),\n",
    "    t_b=-13,\n",
    "    t_of=13,\n",
    "    t_ob=6,\n",
    "    verbose=False,\n",
    "    **kwargs\n",
    "):\n",
    "    \"\"\"Cost function based on free-energy\n",
    "\n",
    "    Args:\n",
    "        sRNA: small RNA sequence\n",
    "        preAUG: sequence of pre-AUG region\n",
    "        cds: coding sequence\n",
    "        region: region (i, j) on which define the open free energy\n",
    "    \"\"\"\n",
    "    i, j, k, l, Eb = rri.RNAup(sRNA, mRNA)\n",
    "    # Add a penalty to ensure interaction stops at least 5nt before SD, starts before pos 60 (adjust as needed for your design)\n",
    "    max_j = rri.PARAMS[\"SD_pos\"] - 5\n",
    "    max_i = 60\n",
    "    if j >= max_j:\n",
    "        Eb = Eb + (j - max_j + 1)\n",
    "    if i >= max_i:\n",
    "        Eb = Eb + (i - max_i + 1)\n",
    "\n",
    "    open_free = rri.dGopen(mRNA, region)\n",
    "    open_bound = rri.dGopen(mRNA, region, [i, j])\n",
    "    # print( i,j ,mRNA[188:218])\n",
    "\n",
    "    # normalize features\n",
    "    b, of, ob, delta = (\n",
    "        (Eb - t_b) / 5,\n",
    "        (-open_free + t_of) / 5,\n",
    "        (open_bound - t_ob) / 5,\n",
    "        (open_bound - open_free + t_of - t_ob) / 3,\n",
    "    )\n",
    "    if verbose:\n",
    "        print(\n",
    "            \"energies[binding,dGfree,dGbound,(dGdiff)]: {:6.2f} {:6.2f} {:6.2f}\".format(Eb, open_free, open_bound),\n",
    "            \"\\t\", \n",
    "            \"normalized + weighted: {:6.2f} {:6.2f} {:6.2f} {:6.2f}\".format(b, of, ob, delta)\n",
    "        )\n",
    "    return LogSumExp(b, of, ob, delta)\n",
    "\n",
    "\n",
    "# apply cost function to DsrA-rpoS example\n",
    "cost_dG(dsra_seq, rpos_seq, verbose=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d01bb0f0-d34f-4e81-9a96-3958a402bccb",
   "metadata": {},
   "source": [
    "### Generate design with thermodynamic cost function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "71d9eb2b-7965-4f75-b379-2ed2fccb33cc",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GGAGUGAGCUCGUUGUGUGGGCUUGCACUUCAGAAUUCGUUGCAGGGGGAGGUUGUUCGGCCGUUUCGAAGGCCUAGGUCAUUUCGGUCGAUCUUAGCUUCCCUGCUAAUCCUCACUUACCCCGACCGGUUGGGCGACAGGAGCCUCCCUAUGAGUAAAGGAGAAGAACUUUUCACU 2.6081930714340213\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.76   9.56   8.73 \t normalized + weighted:   0.45   0.69   0.55   2.05\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GGAGUGAGCUCGUUGUGUGGGCUUGCACUUCAGAAUUCGUUGCAGGGGGAGGUUGUUCGGCCGUUUCGAAGGCCUAGGUCAUUUCGGUCGAUCUUAGCUUCCCUGCUAAUCCUCACUUACCCCGCCCGGUUGGGCGACAGGAGCCUCCCUAUGAGUAAAGGAGAAGAACUUUUCACU 2.571501087758453\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.38   7.77   6.18 \t normalized + weighted:   0.72   1.05   0.04   1.81\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GGAGUGAGGUCGUUGUGUGGGCUUGCACUUCAGAAUUCGUUGCAGGGGGAGGUUGUUCGGCCGUUUCGAAGGCCUAGGUCAUUUCGGUCGAUCUUAGCUUCCCUGCUAAUCCUCACUUACCCCGCCCGGUUGGGCGACAGGAGCCUCCCUAUGAGUAAAGGAGAAGAACUUUUCACU 2.4872805776867306\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.48   8.77   6.29 \t normalized + weighted:   0.90   0.85   0.06   1.51\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GGAGUGAGGUCGUUGUGUGGGCUUGCACUUCAGAAUUCGUUGCAGGGGGAGGUUGUUCGGCCAUUUCGAAGGCCUAGGUCAUUUCGGUCGAUCUUAGCUUCCCUGCUAAUCCUCACUUACCCCGCCUGGUUGGGCGACAGGAGCCUCCCUAUGAGUAAAGGAGAAGAACUUUUCACU 2.338532869973482\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.73  11.35   8.73 \t normalized + weighted:   1.05   0.33   0.55   1.46\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GGAGUGAGGUCGUUGUGUGGGCUUGCACUUCAGAAUUCGUUGCAGGGGGAGGUUAUUCGGCCAUUUCGAAGGCCUAGGUCAUUUCGGUCGAUCUUAGCUUCCCUGCUAAUCCUCACUUACCCCGCCUGGUUGGGUGACAGGAGCCUCCCUAUGAGUAAAGGAGAAGAACUUUUCACU 2.331373494758607\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.73  12.03  10.60 \t normalized + weighted:   1.05   0.19   0.92   1.86\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.28  11.47  10.70 \t normalized + weighted:   0.74   0.31   0.94   2.08\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.28  11.65  10.86 \t normalized + weighted:   0.74   0.27   0.97   2.07\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.28  12.27  11.65 \t normalized + weighted:   0.74   0.15   1.13   2.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.53  11.44  11.55 \t normalized + weighted:   0.49   0.31   1.11   2.37\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.92   9.53   9.47 \t normalized + weighted:   0.22   0.69   0.69   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.90   9.57   9.47 \t normalized + weighted:   0.22   0.69   0.69   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.74   9.68   9.43 \t normalized + weighted:   0.05   0.66   0.69   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.02   9.68   9.61 \t normalized + weighted:  -0.00   0.66   0.72   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.15   9.71   8.91 \t normalized + weighted:  -0.23   0.66   0.58   2.07\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.83   8.07   8.04 \t normalized + weighted:  -0.97   0.99   0.41   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.86   8.51   8.51 \t normalized + weighted:  -0.97   0.90   0.50   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.86   8.47   8.47 \t normalized + weighted:  -0.97   0.91   0.49   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.59  12.02   9.41 \t normalized + weighted:  -0.32   0.20   0.68   1.46\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GAAAUGAGGUCGUUGUGAGGGCUUGCACUUCAGAAUUCGUUGCAGGGGGAGGUCACUCGGCACUUUCGGCGGCCUAGGUCAUUUCGGUCCAUCUUAGCUUCGCUGCUAAUCCUCACUUAUCCGGCCGUGUUGGGUGACAGGAGCCUCCCUAUGAGUAAAGGAGAAGAACUUUUCACU 2.1099358100892296\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.83  11.33   9.33 \t normalized + weighted:  -0.17   0.33   0.67   1.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.52  12.33  12.58 \t normalized + weighted:   0.50   0.13   1.32   2.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.35  10.42   9.33 \t normalized + weighted:  -0.07   0.52   0.67   1.97\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.90   9.94   9.33 \t normalized + weighted:  -0.18   0.61   0.67   2.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.80  10.36   9.65 \t normalized + weighted:  -0.16   0.53   0.73   2.10\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.58  10.37   9.46 \t normalized + weighted:  -0.12   0.53   0.69   2.03\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.52  10.36   9.38 \t normalized + weighted:  -0.10   0.53   0.68   2.01\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.79  10.96  10.87 \t normalized + weighted:  -0.36   0.41   0.97   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.68  11.17  10.04 \t normalized + weighted:   0.06   0.37   0.81   1.96\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.79   9.34   9.32 \t normalized + weighted:  -0.16   0.73   0.66   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.08   9.23   8.36 \t normalized + weighted:  -0.02   0.75   0.47   2.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.62  10.76  10.22 \t normalized + weighted:  -0.12   0.45   0.84   2.15\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.70  10.45  10.22 \t normalized + weighted:   0.66   0.51   0.84   2.26\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.42   9.71  10.04 \t normalized + weighted:  -0.08   0.66   0.81   2.45\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.23  10.05  10.05 \t normalized + weighted:  -0.25   0.59   0.81   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.47   8.88  11.00 \t normalized + weighted:   0.11   0.82   1.00   3.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.21  10.06  10.05 \t normalized + weighted:  -0.24   0.59   0.81   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.18  10.09  10.07 \t normalized + weighted:  -0.24   0.58   0.81   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.22  10.07  10.07 \t normalized + weighted:  -0.24   0.59   0.81   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.89  10.37  10.06 \t normalized + weighted:  -0.18   0.53   0.81   2.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.37  11.65  10.09 \t normalized + weighted:   0.13   0.27   0.82   1.81\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.08  10.14  10.02 \t normalized + weighted:  -0.22   0.57   0.80   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.07  10.11   9.99 \t normalized + weighted:  -0.21   0.58   0.80   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.32  10.61   9.12 \t normalized + weighted:   0.14   0.48   0.62   1.84\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.79  10.36   9.12 \t normalized + weighted:   0.04   0.53   0.62   1.92\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.01  10.16   9.15 \t normalized + weighted:  -0.00   0.57   0.63   2.00\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.39   9.96   9.31 \t normalized + weighted:  -0.08   0.61   0.66   2.12\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.33  11.19  10.51 \t normalized + weighted:  -0.07   0.36   0.90   2.11\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.52  10.59  10.13 \t normalized + weighted:   0.10   0.48   0.83   2.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.49   9.96   8.31 \t normalized + weighted:   0.50   0.61   0.46   1.78\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.44   9.97   8.26 \t normalized + weighted:   0.51   0.61   0.45   1.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.66   9.78   8.34 \t normalized + weighted:   0.67   0.64   0.47   1.85\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.60   9.99   8.27 \t normalized + weighted:   0.48   0.60   0.45   1.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.16  11.92   8.70 \t normalized + weighted:   0.37   0.22   0.54   1.26\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GAAAUGUGGUCGCUGACCACGUUUGUACUUCGGAAUUCGUUGCAGGGGGAGGUUAGUCGGCACUUUCGGCGGCCUAGGUCAUUUCGUUCCAUCUAAGGUACGCUGCAAGUACUGACUUAUCCGGGAGUGUUGGUUAACAGGAGCCUCUCUAUGAGUAAAGGAGAAGAACUUUUCACU 2.0706106767112846\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.91  12.08   8.67 \t normalized + weighted:   0.42   0.18   0.53   1.19\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GAAAUGUGGUCGCUGACCACGUUUGUACUUCGGAAUUCGUUGCAGGGGGAGGUUAGUCGGCACUUUCGGCGGCCUACGUCAUUUCGUUCCAUCUAAGGUACGCUGCAAGUACUGACUUAUCCGGGAGUGUUGGUUAACAGGAGCCUCUCUAUGAGUAAAGGAGAAGAACUUUUCACU 2.044940520358462\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.56  12.29   8.60 \t normalized + weighted:   0.49   0.14   0.52   1.10\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GAAAUGUGGUCGCUGACCACGUUUGUACUUCGGAAUUCGUUGCAGGGGGAGGUUAGUCGGCACUUUCGGCGGCCUACAUCAUUUCGUUCCAUCUAAGGUACGCUGCAAGUACUGACUUAUCCGGGAGUGUUGGUUAACAGGAGCCUCUCUAUGAGUAAAGGAGAAGAACUUUUCACU 2.0116436634917823\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.93  13.58   8.58 \t normalized + weighted:   0.81  -0.12   0.52   0.67\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GAAAUGUGGUCGCUGACCAAGUUUGUACUUCGGAAUUCGUUGCAGGGGGAGGUUAGUCGGCACUUUCGGCGGCCUACAUCAUUUCGUUCCAUCUAAGGUACGCUGCAAGUACUGACUUAUCCGGGAGUGUUGGUUAACAGGAGCCUCUCUAUGAGUAAAGGAGAAGAACUUUUCACU 1.9128269602801662\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.20  11.47  10.77 \t normalized + weighted:   0.56   0.31   0.95   2.10\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.00  11.13  10.10 \t normalized + weighted:   0.80   0.37   0.82   1.99\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.95  11.15  11.13 \t normalized + weighted:   0.81   0.37   1.03   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.60  11.47  10.90 \t normalized + weighted:   1.08   0.31   0.98   2.14\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.61  12.64  10.90 \t normalized + weighted:   1.08   0.07   0.98   1.75\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.61  12.84  10.87 \t normalized + weighted:   1.08   0.03   0.97   1.68\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.60  12.92  10.86 \t normalized + weighted:   1.08   0.02   0.97   1.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.63  12.85  10.85 \t normalized + weighted:   1.07   0.03   0.97   1.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.63  12.80  10.85 \t normalized + weighted:   1.07   0.04   0.97   1.68\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.59  12.92  10.86 \t normalized + weighted:   1.08   0.02   0.97   1.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.59  12.92  10.86 \t normalized + weighted:   1.08   0.02   0.97   1.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.46  13.54  12.67 \t normalized + weighted:   0.91  -0.11   1.33   2.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.02  12.32  10.87 \t normalized + weighted:   1.20   0.14   0.97   1.85\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.59  12.90  10.86 \t normalized + weighted:   1.08   0.02   0.97   1.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  52.24  12.58  12.92 \t normalized + weighted:  13.05   0.08   1.38   2.45\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.87  10.28  11.17 \t normalized + weighted:   0.83   0.54   1.03   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.87  10.28  11.17 \t normalized + weighted:   0.83   0.54   1.03   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.11  10.14  11.13 \t normalized + weighted:   0.78   0.57   1.03   2.66\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.87  10.28  11.17 \t normalized + weighted:   0.83   0.54   1.03   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.10  10.03  11.17 \t normalized + weighted:   0.78   0.59   1.03   2.71\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.72  10.38  11.22 \t normalized + weighted:   0.86   0.52   1.04   2.61\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.97   9.49   9.51 \t normalized + weighted:   1.01   0.70   0.70   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.36   8.63   8.04 \t normalized + weighted:   1.13   0.87   0.41   2.14\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.35  11.33   9.59 \t normalized + weighted:   1.13   0.33   0.72   1.75\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.12  11.75   9.63 \t normalized + weighted:   1.18   0.25   0.73   1.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.76  11.54  10.15 \t normalized + weighted:   1.25   0.29   0.83   1.87\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.14  11.54  11.41 \t normalized + weighted:   0.97   0.29   1.08   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.16  11.55  11.52 \t normalized + weighted:   0.97   0.29   1.10   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.31  11.56  11.69 \t normalized + weighted:   0.94   0.29   1.14   2.38\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.14  11.35  11.60 \t normalized + weighted:   0.97   0.33   1.12   2.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.33  11.68  11.83 \t normalized + weighted:   0.93   0.26   1.17   2.38\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.36  12.74  12.91 \t normalized + weighted:   0.93   0.05   1.38   2.39\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.98  11.80  12.91 \t normalized + weighted:   0.60   0.24   1.38   2.70\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.74  12.11  11.91 \t normalized + weighted:   0.65   0.18   1.18   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.41  12.31  12.11 \t normalized + weighted:   0.72   0.14   1.22   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.10  12.96  12.11 \t normalized + weighted:   0.78   0.01   1.22   2.05\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.89  13.70  12.11 \t normalized + weighted:   1.02  -0.14   1.22   1.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.76  13.73  12.22 \t normalized + weighted:   1.05  -0.15   1.24   1.83\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.08  11.84  11.26 \t normalized + weighted:   0.98   0.23   1.05   2.14\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.08  11.82  11.26 \t normalized + weighted:   0.98   0.24   1.05   2.15\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.07  11.82  11.27 \t normalized + weighted:   0.99   0.24   1.05   2.15\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.01  10.88  10.81 \t normalized + weighted:   0.80   0.42   0.96   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.30  10.89  10.78 \t normalized + weighted:   0.74   0.42   0.96   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.26  10.90  10.78 \t normalized + weighted:   0.75   0.42   0.96   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.74  11.13  10.81 \t normalized + weighted:   0.65   0.37   0.96   2.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.11  11.20  11.36 \t normalized + weighted:   0.58   0.36   1.07   2.39\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.23  11.20  11.04 \t normalized + weighted:   0.75   0.36   1.01   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.87  10.72  10.72 \t normalized + weighted:   0.83   0.46   0.94   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.62  10.72  10.72 \t normalized + weighted:   0.88   0.46   0.94   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.62  10.75  10.75 \t normalized + weighted:   0.88   0.45   0.95   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.62  10.92  10.92 \t normalized + weighted:   0.88   0.42   0.98   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.62  10.92  10.92 \t normalized + weighted:   0.88   0.42   0.98   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.62  10.88  10.88 \t normalized + weighted:   0.88   0.42   0.98   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.61  11.35  11.34 \t normalized + weighted:   0.88   0.33   1.07   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.63  10.88  10.88 \t normalized + weighted:   0.87   0.42   0.98   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.63  10.96  10.96 \t normalized + weighted:   0.87   0.41   0.99   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.63  11.13  11.13 \t normalized + weighted:   0.87   0.37   1.03   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.13  11.13  11.13 \t normalized + weighted:   0.97   0.37   1.03   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.94  11.10  10.90 \t normalized + weighted:   0.81   0.38   0.98   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.07  11.04  10.88 \t normalized + weighted:   0.79   0.39   0.98   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.89  10.91  10.85 \t normalized + weighted:   0.82   0.42   0.97   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.21  10.88  10.85 \t normalized + weighted:   0.96   0.42   0.97   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.23  10.87  10.83 \t normalized + weighted:   0.95   0.43   0.97   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.09  10.87  10.83 \t normalized + weighted:   1.18   0.43   0.97   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.44  10.87  10.83 \t normalized + weighted:   1.11   0.43   0.97   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.43  11.42  11.42 \t normalized + weighted:   1.11   0.32   1.08   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.46  11.47  11.45 \t normalized + weighted:   1.11   0.31   1.09   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.58  11.83  11.62 \t normalized + weighted:   0.88   0.23   1.12   2.26\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.62  11.86  11.56 \t normalized + weighted:   0.88   0.23   1.11   2.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.25  11.88  11.56 \t normalized + weighted:   0.95   0.22   1.11   2.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.69  11.89  11.81 \t normalized + weighted:   0.86   0.22   1.16   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.15  11.92  11.71 \t normalized + weighted:   0.77   0.22   1.14   2.26\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.54  11.87  11.70 \t normalized + weighted:   0.69   0.23   1.14   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.43  11.66  11.37 \t normalized + weighted:   0.71   0.27   1.07   2.24\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.70  10.80  10.71 \t normalized + weighted:   0.66   0.44   0.94   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.94  11.52  12.98 \t normalized + weighted:   0.41   0.30   1.40   2.82\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.71  11.41  14.72 \t normalized + weighted:   0.26   0.32   1.74   3.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.31  12.60  11.16 \t normalized + weighted:   0.94   0.08   1.03   1.85\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.96  10.91  12.03 \t normalized + weighted:   0.61   0.42   1.21   2.71\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.59  10.66  10.46 \t normalized + weighted:   0.68   0.47   0.89   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.62  10.63  10.46 \t normalized + weighted:   0.68   0.47   0.89   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.61  10.64  10.46 \t normalized + weighted:   0.68   0.47   0.89   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.50  10.75  10.46 \t normalized + weighted:   0.70   0.45   0.89   2.24\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.53  10.70  10.46 \t normalized + weighted:   0.69   0.46   0.89   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.30  10.43  10.47 \t normalized + weighted:   0.74   0.51   0.89   2.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.07   9.18  10.41 \t normalized + weighted:   1.19   0.76   0.88   2.74\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.24   9.27  11.52 \t normalized + weighted:   1.15   0.75   1.10   3.08\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.52   8.87  10.36 \t normalized + weighted:   0.90   0.83   0.87   2.83\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.54   9.10  10.48 \t normalized + weighted:   0.89   0.78   0.90   2.79\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.70  10.51   9.70 \t normalized + weighted:   0.66   0.50   0.74   2.07\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.42  11.03  11.58 \t normalized + weighted:   0.92   0.39   1.12   2.52\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.57  12.59  11.58 \t normalized + weighted:   0.89   0.08   1.12   2.00\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.85  12.30  12.00 \t normalized + weighted:   0.83   0.14   1.20   2.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.88  12.25  12.00 \t normalized + weighted:   0.82   0.15   1.20   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.82   9.45  10.35 \t normalized + weighted:   1.04   0.71   0.87   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.06   9.21   9.71 \t normalized + weighted:   1.19   0.76   0.74   2.50\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.13   9.14   9.70 \t normalized + weighted:   1.17   0.77   0.74   2.52\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.81   9.15   9.43 \t normalized + weighted:   1.24   0.77   0.69   2.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.02  10.27  11.39 \t normalized + weighted:   0.80   0.55   1.08   2.70\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.09  10.29  11.28 \t normalized + weighted:   0.78   0.54   1.06   2.66\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.02  10.25  11.64 \t normalized + weighted:   0.80   0.55   1.13   2.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.43  10.77  11.64 \t normalized + weighted:   0.91   0.45   1.13   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.43  10.77  11.57 \t normalized + weighted:   0.91   0.45   1.11   2.60\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.74   9.92  11.87 \t normalized + weighted:   0.85   0.62   1.17   2.98\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.43  10.00  12.10 \t normalized + weighted:   0.91   0.60   1.22   3.03\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.51   9.86  12.13 \t normalized + weighted:   0.90   0.63   1.23   3.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.96   9.85  11.51 \t normalized + weighted:   1.21   0.63   1.10   2.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.63   9.85  12.13 \t normalized + weighted:   1.27   0.63   1.23   3.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.59   9.85  12.07 \t normalized + weighted:   1.28   0.63   1.21   3.07\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.24   9.85  10.56 \t normalized + weighted:   1.55   0.63   0.91   2.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: 130.48  10.74   9.48 \t normalized + weighted:  28.70   0.45   0.70   1.91\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.52   9.85  11.86 \t normalized + weighted:   1.50   0.63   1.17   3.00\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.24   9.85  10.56 \t normalized + weighted:   1.55   0.63   0.91   2.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.24   9.85  10.56 \t normalized + weighted:   1.55   0.63   0.91   2.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.23   9.86  10.57 \t normalized + weighted:   1.55   0.63   0.91   2.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.24   9.85  10.56 \t normalized + weighted:   1.55   0.63   0.91   2.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.36   9.94  10.56 \t normalized + weighted:   1.53   0.61   0.91   2.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: 130.94  10.27   8.54 \t normalized + weighted:  28.79   0.55   0.51   1.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.36   9.94  10.56 \t normalized + weighted:   1.53   0.61   0.91   2.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.36   9.94  10.56 \t normalized + weighted:   1.53   0.61   0.91   2.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: 130.02   9.68   8.87 \t normalized + weighted:  28.60   0.66   0.57   2.06\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.31  10.16   9.96 \t normalized + weighted:   1.54   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.31  10.16   9.96 \t normalized + weighted:   1.54   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.31  10.16   9.96 \t normalized + weighted:   1.54   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: 130.09  10.05   9.17 \t normalized + weighted:  28.62   0.59   0.63   2.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.31  10.16   9.96 \t normalized + weighted:   1.54   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.31  10.16   9.96 \t normalized + weighted:   1.54   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: 130.11  10.07   9.18 \t normalized + weighted:  28.62   0.59   0.64   2.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.31  10.16   9.96 \t normalized + weighted:   1.54   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.31  10.16   9.96 \t normalized + weighted:   1.54   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.31  10.16   9.96 \t normalized + weighted:   1.54   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.45  10.14   9.96 \t normalized + weighted:   1.51   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.45  10.14   9.96 \t normalized + weighted:   1.51   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.45  10.14   9.96 \t normalized + weighted:   1.51   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: 130.14  10.10   9.17 \t normalized + weighted:  28.63   0.58   0.63   2.03\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.45  10.14   9.96 \t normalized + weighted:   1.51   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.45  10.14   9.96 \t normalized + weighted:   1.51   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: 130.09  10.04   9.17 \t normalized + weighted:  28.62   0.59   0.63   2.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.45  10.14   9.96 \t normalized + weighted:   1.51   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.45  10.14   9.96 \t normalized + weighted:   1.51   0.57   0.79   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.57  10.03   9.96 \t normalized + weighted:   1.49   0.59   0.79   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.98  10.03  10.33 \t normalized + weighted:   1.40   0.59   0.87   2.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.98  10.03  10.33 \t normalized + weighted:   1.40   0.59   0.87   2.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.98  10.03  10.33 \t normalized + weighted:   1.40   0.59   0.87   2.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.99  10.03  10.27 \t normalized + weighted:   1.40   0.59   0.85   2.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  29.98  10.03  10.03 \t normalized + weighted:   8.60   0.59   0.81   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.01  10.03  10.14 \t normalized + weighted:   1.40   0.59   0.83   2.37\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  30.47  10.09  10.09 \t normalized + weighted:   8.69   0.58   0.82   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  30.47  10.02  10.02 \t normalized + weighted:   8.69   0.60   0.80   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.70  10.04  10.14 \t normalized + weighted:   1.26   0.59   0.83   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.70  10.06   9.10 \t normalized + weighted:   1.06   0.59   0.62   2.02\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.66  10.03   9.81 \t normalized + weighted:   0.67   0.59   0.76   2.26\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.14  10.06   9.88 \t normalized + weighted:   0.77   0.59   0.78   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.41   9.95   9.77 \t normalized + weighted:   0.52   0.61   0.75   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.76  10.06  10.00 \t normalized + weighted:   0.85   0.59   0.80   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.14  10.01   9.78 \t normalized + weighted:   0.57   0.60   0.76   2.26\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.66  11.65  14.07 \t normalized + weighted:   0.07   0.27   1.61   3.14\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.69  11.62  14.08 \t normalized + weighted:   0.06   0.28   1.62   3.15\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.83  11.48  14.07 \t normalized + weighted:   0.03   0.30   1.61   3.20\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.28   9.23   9.27 \t normalized + weighted:   0.54   0.75   0.65   2.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.72   9.24   9.27 \t normalized + weighted:   0.26   0.75   0.65   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.52   9.17   9.26 \t normalized + weighted:   0.30   0.77   0.65   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.38   8.96   9.72 \t normalized + weighted:   0.12   0.81   0.74   2.59\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.75   9.45   9.77 \t normalized + weighted:   0.25   0.71   0.75   2.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.20   9.68   9.77 \t normalized + weighted:   0.16   0.66   0.75   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.25   9.81   9.78 \t normalized + weighted:   0.15   0.64   0.76   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.74  10.00   9.78 \t normalized + weighted:   0.65   0.60   0.76   2.26\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.35   9.45   9.78 \t normalized + weighted:   0.73   0.71   0.76   2.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.48   9.79  11.48 \t normalized + weighted:   0.90   0.64   1.10   2.90\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.20   9.63   9.63 \t normalized + weighted:   1.36   0.67   0.73   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.20  11.41  11.41 \t normalized + weighted:   1.36   0.32   1.08   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -4.98  11.41  11.76 \t normalized + weighted:   1.60   0.32   1.15   2.45\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.31  11.62  11.51 \t normalized + weighted:   1.34   0.28   1.10   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.14   8.88   7.95 \t normalized + weighted:   0.97   0.82   0.39   2.02\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.03   8.88   7.95 \t normalized + weighted:   0.99   0.82   0.39   2.02\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.12   8.01   7.87 \t normalized + weighted:   0.78   1.00   0.37   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.81  10.06  11.02 \t normalized + weighted:   0.44   0.59   1.00   2.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.77  12.15  11.23 \t normalized + weighted:   0.45   0.17   1.05   2.03\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.97  12.16  11.36 \t normalized + weighted:   0.41   0.17   1.07   2.07\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.53  12.20  12.29 \t normalized + weighted:   0.49   0.16   1.26   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.17  12.14  11.37 \t normalized + weighted:   0.57   0.17   1.07   2.08\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.06  12.27  12.88 \t normalized + weighted:   0.59   0.15   1.38   2.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.00  13.79  14.02 \t normalized + weighted:   0.20  -0.16   1.60   2.41\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.02  13.96  13.99 \t normalized + weighted:   0.20  -0.19   1.60   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.02  14.04  14.04 \t normalized + weighted:   0.20  -0.21   1.61   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.01  11.75  14.02 \t normalized + weighted:   0.20   0.25   1.60   3.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.02  14.02  14.04 \t normalized + weighted:   0.20  -0.20   1.61   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.49   9.77  10.01 \t normalized + weighted:   0.10   0.65   0.80   2.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.49   9.82  10.06 \t normalized + weighted:   0.10   0.64   0.81   2.41\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.50  10.45  10.73 \t normalized + weighted:   0.10   0.51   0.95   2.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.11   9.22   6.36 \t normalized + weighted:  -0.62   0.76   0.07   1.38\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.50   8.10   4.93 \t normalized + weighted:  -0.70   0.98  -0.21   1.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.07   8.37   4.92 \t normalized + weighted:  -0.81   0.93  -0.22   1.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.39   9.90   8.22 \t normalized + weighted:  -0.68   0.62   0.44   1.77\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.61  10.03   8.22 \t normalized + weighted:  -0.52   0.59   0.44   1.73\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.53  10.96   8.22 \t normalized + weighted:  -0.71   0.41   0.44   1.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.52  10.94   8.24 \t normalized + weighted:  -0.70   0.41   0.45   1.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.84   9.78   7.97 \t normalized + weighted:  -0.57   0.64   0.39   1.73\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.02   9.93   7.55 \t normalized + weighted:  -0.40   0.61   0.31   1.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.46   9.28   8.55 \t normalized + weighted:  -0.09   0.74   0.51   2.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.48   9.17   8.59 \t normalized + weighted:  -0.10   0.77   0.52   2.14\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.66   9.27   9.49 \t normalized + weighted:  -0.53   0.75   0.70   2.41\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.30   9.73   9.49 \t normalized + weighted:  -0.66   0.65   0.70   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.00   9.90   9.20 \t normalized + weighted:  -0.60   0.62   0.64   2.10\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.18   9.85   9.51 \t normalized + weighted:  -0.84   0.63   0.70   2.22\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -19.35   9.90   9.75 \t normalized + weighted:  -1.27   0.62   0.75   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -19.71   9.21   9.65 \t normalized + weighted:  -1.34   0.76   0.73   2.48\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.08  10.43  11.39 \t normalized + weighted:  -0.62   0.51   1.08   2.66\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.09  10.94  11.36 \t normalized + weighted:  -0.62   0.41   1.07   2.47\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.08  10.84  12.05 \t normalized + weighted:  -0.62   0.43   1.21   2.73\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.10   9.47   8.24 \t normalized + weighted:  -0.62   0.71   0.45   1.93\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.14   8.92   7.69 \t normalized + weighted:  -0.63   0.82   0.34   1.92\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.83   9.56  11.62 \t normalized + weighted:  -1.17   0.69   1.12   3.02\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.05  13.02  12.41 \t normalized + weighted:  -0.61  -0.00   1.28   2.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.05  12.49  10.94 \t normalized + weighted:  -0.61   0.10   0.99   1.82\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.05  12.51  10.96 \t normalized + weighted:  -0.61   0.10   0.99   1.81\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.27  12.12  10.81 \t normalized + weighted:  -0.45   0.18   0.96   1.90\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.96  12.47  12.01 \t normalized + weighted:  -0.79   0.11   1.20   2.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.05  12.60  11.04 \t normalized + weighted:  -0.61   0.08   1.01   1.81\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.44  10.67  10.24 \t normalized + weighted:  -0.29   0.47   0.85   2.19\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.75  11.90  11.04 \t normalized + weighted:  -0.75   0.22   1.01   2.05\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.71  11.60  10.98 \t normalized + weighted:  -0.54   0.28   1.00   2.12\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.71  11.62  10.99 \t normalized + weighted:  -0.54   0.28   1.00   2.12\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.71  11.62  10.99 \t normalized + weighted:  -0.54   0.28   1.00   2.12\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.71  10.52   9.89 \t normalized + weighted:  -0.54   0.50   0.78   2.12\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.72  10.54   9.92 \t normalized + weighted:  -0.54   0.49   0.78   2.12\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.89   9.28   8.39 \t normalized + weighted:  -0.58   0.74   0.48   2.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.27   9.39  10.59 \t normalized + weighted:  -1.05   0.72   0.92   2.73\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.28   9.41  10.60 \t normalized + weighted:  -1.06   0.72   0.92   2.73\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.28   9.54  10.72 \t normalized + weighted:  -1.06   0.69   0.94   2.73\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.93  11.13  13.12 \t normalized + weighted:  -1.19   0.37   1.42   3.00\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.55  12.36  11.93 \t normalized + weighted:   0.29   0.13   1.19   2.19\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.61  12.43  12.03 \t normalized + weighted:   0.28   0.11   1.21   2.20\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.38  12.03  11.78 \t normalized + weighted:   0.12   0.19   1.16   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.73  10.30  11.94 \t normalized + weighted:  -0.15   0.54   1.19   2.88\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.84  11.71  10.52 \t normalized + weighted:   0.03   0.26   0.90   1.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.03  10.20  11.94 \t normalized + weighted:   0.19   0.56   1.19   2.92\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.03  10.70  12.28 \t normalized + weighted:   0.19   0.46   1.26   2.86\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.60   9.86  11.42 \t normalized + weighted:   0.28   0.63   1.08   2.85\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.37   9.79  10.81 \t normalized + weighted:   0.33   0.64   0.96   2.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.47   9.19  11.52 \t normalized + weighted:   0.11   0.76   1.10   3.11\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.35   9.16  11.59 \t normalized + weighted:   0.13   0.77   1.12   3.14\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.31   9.36  11.89 \t normalized + weighted:   0.14   0.73   1.18   3.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.93   9.64  11.34 \t normalized + weighted:   0.01   0.67   1.07   2.90\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.59   9.05   8.44 \t normalized + weighted:   0.08   0.79   0.49   2.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.07   9.09   9.74 \t normalized + weighted:  -0.01   0.78   0.75   2.55\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.14   9.00  12.42 \t normalized + weighted:   0.17   0.80   1.28   3.47\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.71   9.95   8.69 \t normalized + weighted:  -0.34   0.61   0.54   1.91\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.10  11.93  11.61 \t normalized + weighted:  -0.42   0.21   1.12   2.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.97  12.02  11.61 \t normalized + weighted:  -0.39   0.20   1.12   2.20\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.89  11.84  11.45 \t normalized + weighted:  -0.38   0.23   1.09   2.20\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.09  11.90  11.45 \t normalized + weighted:  -0.42   0.22   1.09   2.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.33  11.83  11.45 \t normalized + weighted:  -0.27   0.23   1.09   2.21\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.42  11.87  11.32 \t normalized + weighted:  -0.28   0.23   1.06   2.15\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.42  11.78  11.28 \t normalized + weighted:  -0.28   0.24   1.06   2.17\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.43  10.53  10.72 \t normalized + weighted:  -0.29   0.49   0.94   2.40\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.37  10.53  10.65 \t normalized + weighted:  -0.27   0.49   0.93   2.38\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.50  11.00  10.70 \t normalized + weighted:  -0.30   0.40   0.94   2.24\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.77  10.68  10.59 \t normalized + weighted:  -0.35   0.46   0.92   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.07  10.66  10.35 \t normalized + weighted:  -0.21   0.47   0.87   2.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.16   8.64  10.31 \t normalized + weighted:   0.37   0.87   0.86   2.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.88  10.75  10.82 \t normalized + weighted:  -0.38   0.45   0.96   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.21  10.45  10.82 \t normalized + weighted:  -0.24   0.51   0.96   2.46\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.65   7.74   9.99 \t normalized + weighted:  -0.13   1.05   0.80   3.08\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.15  10.40  10.62 \t normalized + weighted:  -0.23   0.52   0.92   2.41\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.82  10.39  10.28 \t normalized + weighted:  -0.16   0.52   0.86   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.27  10.59  10.41 \t normalized + weighted:  -0.25   0.48   0.88   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.91  10.33   9.74 \t normalized + weighted:  -0.18   0.53   0.75   2.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.98  10.13   9.58 \t normalized + weighted:  -0.20   0.57   0.72   2.15\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.79   9.33   9.57 \t normalized + weighted:  -0.36   0.73   0.71   2.41\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.20   9.07   7.12 \t normalized + weighted:  -0.04   0.79   0.22   1.69\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.28  11.09  11.19 \t normalized + weighted:  -0.26   0.38   1.04   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.12  10.90   9.76 \t normalized + weighted:  -0.22   0.42   0.75   1.95\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.02  10.84   9.81 \t normalized + weighted:  -0.20   0.43   0.76   1.99\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.95  10.41   9.81 \t normalized + weighted:  -0.19   0.52   0.76   2.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.08   8.36   9.81 \t normalized + weighted:   0.38   0.93   0.76   2.81\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.53  10.09   8.07 \t normalized + weighted:   0.09   0.58   0.41   1.66\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.50  10.25   8.03 \t normalized + weighted:   0.10   0.55   0.41   1.60\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.80  10.32   8.40 \t normalized + weighted:   0.04   0.54   0.48   1.69\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.46   8.77   7.53 \t normalized + weighted:   0.11   0.85   0.31   1.92\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.24  10.80   7.53 \t normalized + weighted:   1.15   0.44   0.31   1.24\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.93   9.07   7.49 \t normalized + weighted:   0.81   0.79   0.30   1.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.89   9.16   7.54 \t normalized + weighted:   0.82   0.77   0.31   1.79\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.65   7.54   7.54 \t normalized + weighted:   0.87   1.09   0.31   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.98   9.10   7.57 \t normalized + weighted:   0.80   0.78   0.31   1.82\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.76  11.84   7.98 \t normalized + weighted:   1.25   0.23   0.40   1.05\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.76  12.10   7.99 \t normalized + weighted:   1.25   0.18   0.40   0.96\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.76  12.09   8.00 \t normalized + weighted:   1.25   0.18   0.40   0.97\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.75  12.10   8.01 \t normalized + weighted:   1.25   0.18   0.40   0.97\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.31  14.29  11.33 \t normalized + weighted:   1.14  -0.26   1.07   1.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.68  14.13  11.83 \t normalized + weighted:   1.06  -0.23   1.17   1.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.90  13.55  10.95 \t normalized + weighted:   1.22  -0.11   0.99   1.47\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.90  13.66  11.06 \t normalized + weighted:   1.22  -0.13   1.01   1.47\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.23  13.33  11.05 \t normalized + weighted:   1.15  -0.07   1.01   1.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.23  13.39  11.37 \t normalized + weighted:   1.15  -0.08   1.07   1.66\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.27  12.62  11.38 \t normalized + weighted:   1.15   0.08   1.08   1.92\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.27  11.72  11.38 \t normalized + weighted:   1.15   0.26   1.08   2.22\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.27  11.10  10.74 \t normalized + weighted:   1.15   0.38   0.95   2.21\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.46   7.74   6.96 \t normalized + weighted:   1.11   1.05   0.19   2.07\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.33   8.63   7.11 \t normalized + weighted:   0.93   0.87   0.22   1.83\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.32   9.32   8.03 \t normalized + weighted:   0.94   0.74   0.41   1.90\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.52  10.11   8.02 \t normalized + weighted:   1.10   0.58   0.40   1.64\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.24   9.61   7.26 \t normalized + weighted:   1.15   0.68   0.25   1.55\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.82   8.07   7.36 \t normalized + weighted:   0.84   0.99   0.27   2.10\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.40  11.75   7.88 \t normalized + weighted:   1.52   0.25   0.38   1.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.52   7.44   7.34 \t normalized + weighted:   1.10   1.11   0.27   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.52   8.05   7.92 \t normalized + weighted:   1.10   0.99   0.38   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.59   7.62   7.61 \t normalized + weighted:   1.08   1.08   0.32   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.50   7.61   7.61 \t normalized + weighted:   1.50   1.08   0.32   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.50   8.31   8.31 \t normalized + weighted:   1.50   0.94   0.46   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.50   8.48   8.48 \t normalized + weighted:   1.50   0.90   0.50   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.01   8.49   8.48 \t normalized + weighted:   1.40   0.90   0.50   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.91   8.62   8.48 \t normalized + weighted:   1.42   0.88   0.50   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.78   9.18  12.47 \t normalized + weighted:   1.24   0.76   1.29   3.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.03   7.13   7.11 \t normalized + weighted:   1.39   1.17   0.22   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.01   7.85   7.85 \t normalized + weighted:   1.40   1.03   0.37   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  84.64   7.85   3.50 \t normalized + weighted:  19.53   1.03  -0.50   0.88\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.84   7.85   7.85 \t normalized + weighted:   1.43   1.03   0.37   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.85   7.83   7.83 \t normalized + weighted:   1.43   1.03   0.37   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.84   7.83   7.83 \t normalized + weighted:   1.43   1.03   0.37   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  83.65   7.07   2.90 \t normalized + weighted:  19.33   1.19  -0.62   0.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.93   7.83   7.83 \t normalized + weighted:   1.41   1.03   0.37   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  84.63   7.83   3.52 \t normalized + weighted:  19.53   1.03  -0.50   0.90\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.93   7.83   7.83 \t normalized + weighted:   1.41   1.03   0.37   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.75   8.24   8.28 \t normalized + weighted:   1.25   0.95   0.46   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.75   8.24   8.28 \t normalized + weighted:   1.25   0.95   0.46   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.35   8.52   9.42 \t normalized + weighted:   1.13   0.90   0.68   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.36   8.55   9.45 \t normalized + weighted:   1.13   0.89   0.69   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.22   9.89   9.95 \t normalized + weighted:   1.16   0.62   0.79   2.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.41  11.68  12.81 \t normalized + weighted:   1.12   0.26   1.36   2.71\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.41  10.84  11.15 \t normalized + weighted:   1.12   0.43   1.03   2.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.35   9.57   9.87 \t normalized + weighted:   1.13   0.69   0.77   2.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.66   9.89  10.50 \t normalized + weighted:   1.07   0.62   0.90   2.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.34  10.29   9.82 \t normalized + weighted:   1.13   0.54   0.76   2.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.48  10.89  11.57 \t normalized + weighted:   1.10   0.42   1.11   2.56\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.04  10.14  11.15 \t normalized + weighted:   0.99   0.57   1.03   2.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.20   9.26   8.62 \t normalized + weighted:   1.16   0.75   0.52   2.12\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.16   9.90  10.15 \t normalized + weighted:   0.97   0.62   0.83   2.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.21  11.77  12.38 \t normalized + weighted:   1.16   0.25   1.28   2.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.87  12.00  12.29 \t normalized + weighted:   1.23   0.20   1.26   2.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.88  11.97  12.26 \t normalized + weighted:   1.22   0.21   1.25   2.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.00  11.54  12.26 \t normalized + weighted:   1.00   0.29   1.25   2.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.06  11.87  11.87 \t normalized + weighted:   1.19   0.23   1.17   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.06  11.86  11.87 \t normalized + weighted:   1.19   0.23   1.17   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:   2.48  11.98  13.16 \t normalized + weighted:   3.10   0.20   1.43   2.73\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:   2.48  12.50  12.55 \t normalized + weighted:   3.10   0.10   1.31   2.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.09   9.61   8.57 \t normalized + weighted:   0.78   0.68   0.51   1.99\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.94   9.70   9.35 \t normalized + weighted:   1.01   0.66   0.67   2.22\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:   0.61   9.65   9.64 \t normalized + weighted:   2.72   0.67   0.73   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.51   9.33   7.41 \t normalized + weighted:   0.90   0.73   0.28   1.69\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.39   6.83   7.40 \t normalized + weighted:   0.72   1.23   0.28   2.53\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.23   4.63   7.44 \t normalized + weighted:   0.95   1.67   0.29   3.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.61   7.30   7.26 \t normalized + weighted:   0.68   1.14   0.25   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.68   6.85   7.24 \t normalized + weighted:  -0.14   1.23   0.25   2.46\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.94   6.69   7.24 \t normalized + weighted:  -0.19   1.26   0.25   2.52\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.79   6.74   6.95 \t normalized + weighted:  -0.56   1.25   0.19   2.40\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.12   7.79   6.90 \t normalized + weighted:  -0.62   1.04   0.18   2.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.30   8.83  10.24 \t normalized + weighted:   0.34   0.83   0.85   2.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -2.84   6.50   4.97 \t normalized + weighted:   2.03   1.30  -0.21   1.82\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -2.38   7.43   6.11 \t normalized + weighted:   2.12   1.11   0.02   1.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -2.96   6.95   7.07 \t normalized + weighted:   2.01   1.21   0.21   2.37\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -3.00   7.28   7.13 \t normalized + weighted:   2.00   1.14   0.23   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -0.35   7.25   7.13 \t normalized + weighted:   2.53   1.15   0.23   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.61   5.59   7.07 \t normalized + weighted:   0.48   1.48   0.21   2.83\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.92   5.42   7.79 \t normalized + weighted:  -0.18   1.52   0.36   3.12\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.35   7.33   8.63 \t normalized + weighted:  -0.07   1.13   0.53   2.77\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.88   8.01   8.43 \t normalized + weighted:   0.02   1.00   0.49   2.48\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.40   6.93   8.68 \t normalized + weighted:   0.12   1.21   0.54   2.92\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.00   6.87   8.63 \t normalized + weighted:   0.20   1.23   0.53   2.92\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.37   7.03   7.98 \t normalized + weighted:  -1.07   1.19   0.40   2.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.05   5.54   8.17 \t normalized + weighted:  -1.01   1.49   0.43   3.21\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.21   9.62  10.68 \t normalized + weighted:  -1.04   0.68   0.94   2.69\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.21   9.89  10.95 \t normalized + weighted:  -1.04   0.62   0.99   2.69\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.88   9.14  10.94 \t normalized + weighted:  -0.38   0.77   0.99   2.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.86  10.81  10.97 \t normalized + weighted:  -0.37   0.44   0.99   2.38\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.66   9.97  10.94 \t normalized + weighted:  -0.33   0.61   0.99   2.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.90   8.16  10.94 \t normalized + weighted:  -0.78   0.97   0.99   3.26\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.01   7.41  10.57 \t normalized + weighted:  -0.60   1.12   0.91   3.39\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.41   9.19  10.85 \t normalized + weighted:  -0.68   0.76   0.97   2.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.33   8.73  10.56 \t normalized + weighted:  -0.67   0.85   0.91   2.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -19.01   7.16   9.47 \t normalized + weighted:  -1.20   1.17   0.69   3.10\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -19.13   6.62   9.47 \t normalized + weighted:  -1.23   1.28   0.69   3.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.50   5.61   8.94 \t normalized + weighted:  -1.10   1.48   0.59   3.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.88   5.45   8.82 \t normalized + weighted:  -0.98   1.51   0.56   3.46\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.61   6.75  12.08 \t normalized + weighted:   0.48   1.25   1.22   4.11\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.14   5.15   6.17 \t normalized + weighted:   0.57   1.57   0.03   2.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.58   5.16   5.96 \t normalized + weighted:   0.28   1.57  -0.01   2.60\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.92   5.16   5.91 \t normalized + weighted:   0.22   1.57  -0.02   2.58\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.70   5.23   5.91 \t normalized + weighted:   0.46   1.55  -0.02   2.56\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  12.87   6.61   6.17 \t normalized + weighted:   5.17   1.28   0.03   2.19\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.65   6.93   6.09 \t normalized + weighted:   0.47   1.21   0.02   2.05\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.99   6.74   5.86 \t normalized + weighted:   0.40   1.25  -0.03   2.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.07   5.54   5.52 \t normalized + weighted:   0.19   1.49  -0.10   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.10   5.54   5.52 \t normalized + weighted:   0.18   1.49  -0.10   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.14   5.91   5.91 \t normalized + weighted:   0.17   1.42  -0.02   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.14   6.14   6.14 \t normalized + weighted:   0.17   1.37   0.03   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.75   6.15   6.14 \t normalized + weighted:   0.25   1.37   0.03   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.76   7.90   7.97 \t normalized + weighted:   0.25   1.02   0.39   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.54   7.24   7.97 \t normalized + weighted:  -0.31   1.15   0.39   2.58\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.54   7.49   7.95 \t normalized + weighted:  -0.11   1.10   0.39   2.49\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.07   6.78   7.34 \t normalized + weighted:   0.19   1.24   0.27   2.52\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.30   5.37   6.46 \t normalized + weighted:   0.14   1.53   0.09   2.70\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.68   5.80   6.46 \t normalized + weighted:   0.46   1.44   0.09   2.56\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.99   5.20   6.19 \t normalized + weighted:   0.40   1.56   0.04   2.66\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.19   5.17   6.40 \t normalized + weighted:   0.56   1.57   0.08   2.74\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.83   8.03   8.78 \t normalized + weighted:   0.63   0.99   0.56   2.58\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.84   7.57   8.85 \t normalized + weighted:   0.63   1.09   0.57   2.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.76   7.55   8.84 \t normalized + weighted:   0.65   1.09   0.57   2.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.98   7.06   7.50 \t normalized + weighted:   0.80   1.19   0.30   2.48\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.31   7.15   7.73 \t normalized + weighted:   0.54   1.17   0.35   2.52\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.31   7.15   7.73 \t normalized + weighted:   0.54   1.17   0.35   2.53\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.82   7.15   7.14 \t normalized + weighted:  -0.16   1.17   0.23   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.31   6.46   7.81 \t normalized + weighted:  -0.26   1.31   0.36   2.78\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.96   7.05   8.05 \t normalized + weighted:  -0.19   1.19   0.41   2.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.52   7.05   8.05 \t normalized + weighted:  -0.30   1.19   0.41   2.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.53   7.08   8.08 \t normalized + weighted:  -0.31   1.18   0.42   2.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.31   7.27   8.18 \t normalized + weighted:  -0.26   1.15   0.44   2.64\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.70   6.64   7.76 \t normalized + weighted:  -0.34   1.27   0.35   2.71\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.71   5.75   7.81 \t normalized + weighted:  -0.34   1.45   0.36   3.02\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.73   5.10   6.39 \t normalized + weighted:  -0.35   1.58   0.08   2.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.84   4.63   7.52 \t normalized + weighted:  -0.57   1.67   0.30   3.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.64   4.23   7.25 \t normalized + weighted:  -0.53   1.75   0.25   3.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.64   4.23   7.25 \t normalized + weighted:  -0.53   1.75   0.25   3.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.69   4.16   7.60 \t normalized + weighted:  -0.74   1.77   0.32   3.48\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.53   5.05   7.66 \t normalized + weighted:  -0.71   1.59   0.33   3.20\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.05   4.08   4.40 \t normalized + weighted:   0.19   1.78  -0.32   2.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.53   5.77   3.39 \t normalized + weighted:  -0.71   1.45  -0.52   1.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.02   5.24   3.47 \t normalized + weighted:  -0.00   1.55  -0.51   1.74\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.72   5.27   3.46 \t normalized + weighted:  -0.34   1.55  -0.51   1.73\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.71   6.06   3.50 \t normalized + weighted:  -0.14   1.39  -0.50   1.48\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.80   4.10   5.99 \t normalized + weighted:  -0.36   1.78  -0.00   2.97\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.55   4.10   8.53 \t normalized + weighted:  -0.51   1.78   0.51   3.81\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.54   4.53   8.69 \t normalized + weighted:  -0.51   1.69   0.54   3.72\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.25   3.87   8.65 \t normalized + weighted:  -0.25   1.83   0.53   3.93\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.82   3.76   8.65 \t normalized + weighted:  -0.76   1.85   0.53   3.96\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.21   3.73   6.77 \t normalized + weighted:  -0.24   1.85   0.15   3.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.37   3.73   5.95 \t normalized + weighted:  -0.07   1.85  -0.01   3.08\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.68   3.47   6.28 \t normalized + weighted:   0.06   1.91   0.06   3.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.68   3.47   6.28 \t normalized + weighted:   0.06   1.91   0.06   3.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.68   3.47   6.28 \t normalized + weighted:   0.06   1.91   0.06   3.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.69   4.21   5.61 \t normalized + weighted:  -0.74   1.76  -0.08   2.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.70   4.22   5.63 \t normalized + weighted:  -0.74   1.76  -0.07   2.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.69   4.21   5.61 \t normalized + weighted:  -0.74   1.76  -0.08   2.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.69   4.22   5.61 \t normalized + weighted:  -0.74   1.76  -0.08   2.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.83   5.14   5.53 \t normalized + weighted:  -0.97   1.57  -0.09   2.46\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.37   4.97   5.60 \t normalized + weighted:  -0.47   1.61  -0.08   2.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.29   4.63   6.35 \t normalized + weighted:  -0.26   1.67   0.07   2.91\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.37   4.63   6.17 \t normalized + weighted:  -0.27   1.67   0.03   2.85\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.06   5.92   6.61 \t normalized + weighted:  -0.01   1.42   0.12   2.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.23   5.92   6.60 \t normalized + weighted:   0.15   1.42   0.12   2.56\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.45   5.94   6.45 \t normalized + weighted:   0.11   1.41   0.09   2.50\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.11   5.99   6.27 \t normalized + weighted:  -0.02   1.40   0.05   2.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.38   8.03   6.60 \t normalized + weighted:   0.12   0.99   0.12   1.86\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.58   8.60   8.12 \t normalized + weighted:   0.88   0.88   0.42   2.17\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.73   8.99   7.71 \t normalized + weighted:   1.05   0.80   0.34   1.91\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.64   8.86   7.69 \t normalized + weighted:   1.07   0.83   0.34   1.95\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.66   8.78   7.77 \t normalized + weighted:   1.07   0.84   0.35   2.00\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.21   9.46   8.48 \t normalized + weighted:   0.96   0.71   0.50   2.01\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.81   9.34   7.97 \t normalized + weighted:   1.04   0.73   0.39   1.88\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.24  10.16   6.22 \t normalized + weighted:   0.75   0.57   0.04   1.02\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.24  10.16   6.21 \t normalized + weighted:   0.75   0.57   0.04   1.02\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.23  10.16   6.20 \t normalized + weighted:   0.75   0.57   0.04   1.01\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.24  10.14   6.21 \t normalized + weighted:   0.75   0.57   0.04   1.03\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.28   9.92   6.31 \t normalized + weighted:   0.74   0.62   0.06   1.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.46   9.50   6.20 \t normalized + weighted:   0.71   0.70   0.04   1.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.27   8.85   7.67 \t normalized + weighted:   0.55   0.83   0.33   1.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.31   8.82   7.67 \t normalized + weighted:   0.54   0.84   0.33   1.95\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.19   7.41   5.37 \t normalized + weighted:   0.56   1.12  -0.13   1.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.75   5.91   6.26 \t normalized + weighted:   0.45   1.42   0.05   2.45\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.53   7.43   5.40 \t normalized + weighted:   0.29   1.11  -0.12   1.66\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.32   7.84   6.02 \t normalized + weighted:   0.34   1.03   0.00   1.73\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.19   7.99   6.56 \t normalized + weighted:   0.36   1.00   0.11   1.86\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.20   8.18   6.59 \t normalized + weighted:   0.36   0.96   0.12   1.81\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.23   8.11   6.62 \t normalized + weighted:   0.35   0.98   0.12   1.84\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.20   8.08   6.55 \t normalized + weighted:   0.36   0.98   0.11   1.82\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.21   8.04   6.52 \t normalized + weighted:   0.36   0.99   0.10   1.83\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.84   6.60   6.52 \t normalized + weighted:   0.43   1.28   0.10   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.93   7.26   6.64 \t normalized + weighted:   0.41   1.15   0.13   2.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.93   7.73   6.60 \t normalized + weighted:   0.41   1.05   0.12   1.96\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.88   7.01   6.59 \t normalized + weighted:   0.42   1.20   0.12   2.19\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.92   7.38   6.59 \t normalized + weighted:   0.42   1.12   0.12   2.07\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.77   6.01   6.53 \t normalized + weighted:   0.45   1.40   0.11   2.51\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.94   7.29   6.52 \t normalized + weighted:   0.41   1.14   0.10   2.08\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.02   8.46   8.51 \t normalized + weighted:   0.20   0.91   0.50   2.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.18   8.70   8.42 \t normalized + weighted:   0.36   0.86   0.48   2.24\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.49   8.14   6.73 \t normalized + weighted:   0.50   0.97   0.15   1.86\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.55   6.19   7.03 \t normalized + weighted:   0.69   1.36   0.21   2.61\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.71   9.08   9.53 \t normalized + weighted:   0.46   0.78   0.71   2.48\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.21   7.07   7.80 \t normalized + weighted:   0.96   1.19   0.36   2.58\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.49   7.67   8.38 \t normalized + weighted:   0.90   1.07   0.48   2.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.92   7.08   9.54 \t normalized + weighted:   0.62   1.18   0.71   3.16\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.12   6.68   8.49 \t normalized + weighted:   0.78   1.26   0.50   2.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.13   6.71   8.52 \t normalized + weighted:   0.77   1.26   0.50   2.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.99   7.00   9.62 \t normalized + weighted:   0.60   1.20   0.72   3.21\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.34   8.07   9.85 \t normalized + weighted:   0.53   0.99   0.77   2.93\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.75   6.99   9.12 \t normalized + weighted:   0.65   1.20   0.62   3.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.00   7.45   8.12 \t normalized + weighted:   1.00   1.11   0.42   2.55\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.55   7.19   6.65 \t normalized + weighted:   1.29   1.16   0.13   2.15\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.70   7.79   7.98 \t normalized + weighted:   1.46   1.04   0.40   2.40\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.44   8.27   8.20 \t normalized + weighted:   1.51   0.95   0.44   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.07   9.17   8.64 \t normalized + weighted:   1.59   0.77   0.53   2.16\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.98   8.54   8.64 \t normalized + weighted:   1.20   0.89   0.53   2.37\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.09   9.57  10.88 \t normalized + weighted:   1.18   0.69   0.98   2.77\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.08   9.16   9.66 \t normalized + weighted:   1.18   0.77   0.73   2.50\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.75  10.80  12.51 \t normalized + weighted:   1.05   0.44   1.30   2.90\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.76  10.48  12.53 \t normalized + weighted:   1.05   0.50   1.31   3.02\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.45  10.52  12.34 \t normalized + weighted:   1.11   0.50   1.27   2.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.76  11.42  12.52 \t normalized + weighted:   1.05   0.32   1.30   2.70\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.79  11.60  12.67 \t normalized + weighted:   1.04   0.28   1.33   2.69\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.78   9.45  12.76 \t normalized + weighted:   1.04   0.71   1.35   3.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.78  10.96  12.78 \t normalized + weighted:   1.04   0.41   1.36   2.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.75   8.95  12.16 \t normalized + weighted:   1.05   0.81   1.23   3.40\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.75   8.97  12.17 \t normalized + weighted:   1.05   0.81   1.23   3.40\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.65   8.47  10.21 \t normalized + weighted:   0.87   0.91   0.84   2.91\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.69  11.70  13.28 \t normalized + weighted:   0.86   0.26   1.46   2.86\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.97  10.84  15.19 \t normalized + weighted:   1.01   0.43   1.84   3.78\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.63  11.84  12.51 \t normalized + weighted:   1.07   0.23   1.30   2.56\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.13  11.54  13.29 \t normalized + weighted:   1.17   0.29   1.46   2.92\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.55  11.52  12.35 \t normalized + weighted:   1.09   0.30   1.27   2.61\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.69  11.23  12.03 \t normalized + weighted:   0.66   0.35   1.21   2.60\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.86   8.41   8.06 \t normalized + weighted:   0.63   0.92   0.41   2.22\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.70   6.98   8.05 \t normalized + weighted:   0.66   1.20   0.41   2.69\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.49   6.98   8.25 \t normalized + weighted:   0.90   1.20   0.45   2.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.37   6.74   8.26 \t normalized + weighted:   0.93   1.25   0.45   2.84\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.62   6.13   7.32 \t normalized + weighted:   1.28   1.37   0.26   2.73\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.64   6.11   7.32 \t normalized + weighted:   1.27   1.38   0.26   2.74\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.15   6.14   8.32 \t normalized + weighted:   0.77   1.37   0.46   3.06\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.95   4.73   8.17 \t normalized + weighted:  -0.19   1.65   0.43   3.48\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.19   6.14   8.30 \t normalized + weighted:   0.76   1.37   0.46   3.05\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.39   4.34   5.74 \t normalized + weighted:   0.92   1.73  -0.05   2.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.40   4.34   4.58 \t normalized + weighted:   0.72   1.73  -0.28   2.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  98.39   9.06   8.87 \t normalized + weighted:  22.28   0.79   0.57   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.93   4.53   6.16 \t normalized + weighted:   0.81   1.69   0.03   2.88\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.22   4.44   4.51 \t normalized + weighted:   0.76   1.71  -0.30   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.07   6.23   6.23 \t normalized + weighted:   0.59   1.35   0.05   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.36   6.23   6.73 \t normalized + weighted:   0.53   1.35   0.15   2.50\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.82   6.34   6.73 \t normalized + weighted:   0.64   1.33   0.15   2.46\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  98.39  10.20  10.00 \t normalized + weighted:  22.28   0.56   0.80   2.27\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.98   6.34   4.29 \t normalized + weighted:   1.20   1.33  -0.34   1.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.58   4.84   4.46 \t normalized + weighted:   0.88   1.63  -0.31   2.21\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.61   7.29   7.98 \t normalized + weighted:   0.68   1.14   0.40   2.56\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.79   7.29  10.41 \t normalized + weighted:   0.24   1.14   0.88   3.37\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.22   7.29   6.55 \t normalized + weighted:   1.36   1.14   0.11   2.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.20   6.96   7.01 \t normalized + weighted:   1.16   1.21   0.20   2.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.95   7.53   6.95 \t normalized + weighted:   1.01   1.09   0.19   2.14\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.20   6.89   6.95 \t normalized + weighted:   0.76   1.22   0.19   2.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.40   6.65   6.96 \t normalized + weighted:   0.72   1.27   0.19   2.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  76.54   6.62   3.13 \t normalized + weighted:  17.91   1.28  -0.57   1.17\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.07   6.66   6.93 \t normalized + weighted:   0.39   1.27   0.19   2.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.40   6.65   6.96 \t normalized + weighted:   0.72   1.27   0.19   2.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.02   6.65   7.25 \t normalized + weighted:   0.80   1.27   0.25   2.53\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.82   6.46   7.25 \t normalized + weighted:   1.04   1.31   0.25   2.60\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  76.09   6.40   3.12 \t normalized + weighted:  17.82   1.32  -0.58   1.24\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.02   5.53   6.52 \t normalized + weighted:   1.00   1.49   0.10   2.66\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.07   7.48   8.26 \t normalized + weighted:   0.79   1.10   0.45   2.59\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.28   8.64   9.59 \t normalized + weighted:   0.54   0.87   0.72   2.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.38   8.51   7.77 \t normalized + weighted:   0.52   0.90   0.35   2.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.64   8.63   8.32 \t normalized + weighted:   0.67   0.87   0.46   2.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.65   8.77   8.31 \t normalized + weighted:   0.67   0.85   0.46   2.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.36   8.49   9.74 \t normalized + weighted:   0.73   0.90   0.75   2.75\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.86   9.07   8.28 \t normalized + weighted:   0.83   0.79   0.46   2.07\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.80   9.25   8.30 \t normalized + weighted:   0.84   0.75   0.46   2.02\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.59   9.67   8.38 \t normalized + weighted:   0.88   0.67   0.48   1.90\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.83   8.22   8.17 \t normalized + weighted:   0.63   0.96   0.43   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.42   8.49   9.14 \t normalized + weighted:   0.92   0.90   0.63   2.55\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.40   8.33   8.80 \t normalized + weighted:   0.92   0.93   0.56   2.49\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.53   8.38   9.47 \t normalized + weighted:   0.69   0.92   0.69   2.70\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.70   7.85   7.81 \t normalized + weighted:   1.06   1.03   0.36   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.52   7.33   7.10 \t normalized + weighted:   0.90   1.13   0.22   2.26\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.34   7.07   7.14 \t normalized + weighted:   0.93   1.19   0.23   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.03   6.92   7.40 \t normalized + weighted:   0.59   1.22   0.28   2.50\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.86   7.09   7.63 \t normalized + weighted:   0.63   1.18   0.33   2.51\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.09   6.93   7.34 \t normalized + weighted:   0.58   1.21   0.27   2.47\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.95   7.01   7.65 \t normalized + weighted:   0.61   1.20   0.33   2.55\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.52   7.84   8.37 \t normalized + weighted:   0.50   1.03   0.47   2.51\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.83   8.60  11.10 \t normalized + weighted:   0.43   0.88   1.02   3.17\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.63   8.42   9.20 \t normalized + weighted:   0.47   0.92   0.64   2.59\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.43   7.77   9.12 \t normalized + weighted:   0.51   1.05   0.62   2.78\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.43  11.27  13.01 \t normalized + weighted:   0.51   0.35   1.40   2.92\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.82  11.21  13.05 \t normalized + weighted:   0.64   0.36   1.41   2.95\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.70   9.27  10.18 \t normalized + weighted:   0.66   0.75   0.84   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.30   7.92  10.67 \t normalized + weighted:   0.94   1.02   0.93   3.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.82  10.76  12.97 \t normalized + weighted:   1.04   0.45   1.39   3.07\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.57  10.94  13.19 \t normalized + weighted:   0.89   0.41   1.44   3.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.03  13.41  14.87 \t normalized + weighted:   0.59  -0.08   1.77   2.82\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.03  12.36  14.07 \t normalized + weighted:   0.59   0.13   1.61   2.91\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.09   8.19  10.75 \t normalized + weighted:   0.58   0.96   0.95   3.19\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.63   7.47   7.53 \t normalized + weighted:   0.67   1.11   0.31   2.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.59   6.65   7.53 \t normalized + weighted:   0.48   1.27   0.31   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.65   6.63   7.53 \t normalized + weighted:   0.27   1.27   0.31   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.11   7.30   7.65 \t normalized + weighted:   0.38   1.14   0.33   2.45\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.35   7.79   9.09 \t normalized + weighted:   0.33   1.04   0.62   2.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.09   9.41  10.85 \t normalized + weighted:   0.38   0.72   0.97   2.81\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.56   6.07   6.87 \t normalized + weighted:   0.29   1.39   0.17   2.60\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.38   7.30   7.65 \t normalized + weighted:   0.32   1.14   0.33   2.45\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.96   8.76   9.78 \t normalized + weighted:   0.21   0.85   0.76   2.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.59   8.06   9.30 \t normalized + weighted:   0.28   0.99   0.66   2.75\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.51   8.45   9.80 \t normalized + weighted:   0.30   0.91   0.76   2.78\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.30   6.68   8.29 \t normalized + weighted:   0.14   1.26   0.46   2.87\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.89   7.38   8.22 \t normalized + weighted:   0.22   1.12   0.44   2.61\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.77   6.43   7.21 \t normalized + weighted:   0.25   1.31   0.24   2.59\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.95   6.54   7.54 \t normalized + weighted:   0.01   1.29   0.31   2.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.09   6.31   7.65 \t normalized + weighted:  -0.02   1.34   0.33   2.78\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.99   6.55   7.57 \t normalized + weighted:   0.00   1.29   0.31   2.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.74   9.17   9.86 \t normalized + weighted:   0.05   0.77   0.77   2.56\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.22   9.12   9.80 \t normalized + weighted:   0.36   0.78   0.76   2.56\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.52   9.58   9.61 \t normalized + weighted:   0.30   0.68   0.72   2.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.52   9.61   9.62 \t normalized + weighted:   0.30   0.68   0.72   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.52   9.61   9.62 \t normalized + weighted:   0.30   0.68   0.72   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.90  10.25  11.55 \t normalized + weighted:  -0.38   0.55   1.11   2.77\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.52   7.30   8.65 \t normalized + weighted:  -0.30   1.14   0.53   2.78\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.50   8.63   9.27 \t normalized + weighted:  -0.30   0.87   0.65   2.55\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.63   8.46   9.67 \t normalized + weighted:  -0.33   0.91   0.73   2.74\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.63   8.46   9.67 \t normalized + weighted:  -0.33   0.91   0.73   2.74\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.63   8.48   9.69 \t normalized + weighted:  -0.33   0.90   0.74   2.74\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.57   8.41  10.55 \t normalized + weighted:   0.09   0.92   0.91   3.05\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.19   7.86   9.88 \t normalized + weighted:  -0.04   1.03   0.78   3.01\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.23   7.86   9.22 \t normalized + weighted:  -0.05   1.03   0.64   2.79\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.43  10.14  13.59 \t normalized + weighted:  -0.49   0.57   1.52   3.48\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.06  10.94  13.59 \t normalized + weighted:  -1.01   0.41   1.52   3.22\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.69  10.53  11.22 \t normalized + weighted:  -1.14   0.49   1.04   2.56\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -19.15  10.03  13.57 \t normalized + weighted:  -1.23   0.59   1.51   3.51\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.89  10.60  11.23 \t normalized + weighted:  -0.98   0.48   1.05   2.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.57  11.27  11.83 \t normalized + weighted:  -0.71   0.35   1.17   2.52\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -19.42   9.65  11.83 \t normalized + weighted:  -1.28   0.67   1.17   3.06\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -20.03   9.36  11.83 \t normalized + weighted:  -1.41   0.73   1.17   3.16\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -19.58   7.96  10.25 \t normalized + weighted:  -1.32   1.01   0.85   3.10\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -19.37   6.99   7.63 \t normalized + weighted:  -1.27   1.20   0.33   2.55\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.63   7.27   7.13 \t normalized + weighted:  -1.13   1.15   0.23   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.22   6.96   6.81 \t normalized + weighted:  -1.04   1.21   0.16   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.98   9.51   8.76 \t normalized + weighted:  -1.00   0.70   0.55   2.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.93  11.88  11.41 \t normalized + weighted:  -0.99   0.22   1.08   2.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -21.09   8.34  13.19 \t normalized + weighted:  -1.62   0.93   1.44   3.95\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.95  10.89  11.46 \t normalized + weighted:  -0.99   0.42   1.09   2.53\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.96  11.25  11.24 \t normalized + weighted:  -0.99   0.35   1.05   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.95  11.68  11.67 \t normalized + weighted:  -0.99   0.26   1.13   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.96  10.77  11.24 \t normalized + weighted:  -0.99   0.45   1.05   2.49\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.95   9.01   9.00 \t normalized + weighted:  -0.99   0.80   0.60   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.95   8.98   8.98 \t normalized + weighted:  -0.99   0.80   0.60   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.91   7.12   8.38 \t normalized + weighted:  -0.98   1.18   0.48   2.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.95   8.98   8.99 \t normalized + weighted:  -0.99   0.80   0.60   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.94   9.39   9.67 \t normalized + weighted:  -0.99   0.72   0.73   2.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.97   8.97   9.54 \t normalized + weighted:  -0.99   0.81   0.71   2.52\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.49   6.84   9.63 \t normalized + weighted:  -0.70   1.23   0.73   3.26\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.93   8.75   8.85 \t normalized + weighted:  -0.99   0.85   0.57   2.37\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.92   8.53   8.75 \t normalized + weighted:  -0.98   0.89   0.55   2.41\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.04   8.73   8.85 \t normalized + weighted:  -0.21   0.85   0.57   2.38\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.04   9.33   9.44 \t normalized + weighted:  -0.21   0.73   0.69   2.37\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.03   9.35   9.54 \t normalized + weighted:  -0.21   0.73   0.71   2.40\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.04  10.04  10.07 \t normalized + weighted:  -0.21   0.59   0.81   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.97  10.04  10.07 \t normalized + weighted:  -0.99   0.59   0.81   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -19.07  10.65  10.09 \t normalized + weighted:  -1.21   0.47   0.82   2.15\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -19.47  10.81  10.88 \t normalized + weighted:  -1.29   0.44   0.98   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -20.60  10.32  11.27 \t normalized + weighted:  -1.52   0.54   1.05   2.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -19.84   9.01  11.27 \t normalized + weighted:  -1.37   0.80   1.05   3.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -21.03   7.90   8.88 \t normalized + weighted:  -1.61   1.02   0.58   2.66\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -21.02   8.11   7.57 \t normalized + weighted:  -1.60   0.98   0.31   2.15\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -21.36   7.92   7.78 \t normalized + weighted:  -1.67   1.02   0.36   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.63   7.81   7.78 \t normalized + weighted:  -0.93   1.04   0.36   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.71   7.79   7.83 \t normalized + weighted:  -0.94   1.04   0.37   2.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.43  10.29   7.35 \t normalized + weighted:  -0.09   0.54   0.27   1.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.94   8.59   7.23 \t normalized + weighted:  -0.19   0.88   0.25   1.88\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.72   6.80   6.26 \t normalized + weighted:  -0.14   1.24   0.05   2.15\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.80   6.20   5.62 \t normalized + weighted:  -0.16   1.36  -0.08   2.14\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.66   6.17   5.30 \t normalized + weighted:  -0.33   1.37  -0.14   2.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.95   5.92   5.32 \t normalized + weighted:  -0.19   1.42  -0.14   2.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.00   7.38   5.87 \t normalized + weighted:  -0.20   1.12  -0.03   1.83\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.34   5.39   5.36 \t normalized + weighted:  -0.27   1.52  -0.13   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.02   9.52   6.09 \t normalized + weighted:  -0.20   0.70   0.02   1.19\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.02   9.56   6.11 \t normalized + weighted:  -0.20   0.69   0.02   1.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.02   9.56   6.11 \t normalized + weighted:  -0.20   0.69   0.02   1.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.53   9.45   6.15 \t normalized + weighted:  -0.11   0.71   0.03   1.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.93   6.33   6.08 \t normalized + weighted:  -0.39   1.33   0.02   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.53   9.45   6.15 \t normalized + weighted:  -0.11   0.71   0.03   1.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.52   9.46   6.15 \t normalized + weighted:  -0.10   0.71   0.03   1.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.51   9.46   6.15 \t normalized + weighted:  -0.10   0.71   0.03   1.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.87   9.02   9.13 \t normalized + weighted:  -0.77   0.80   0.63   2.37\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.78   6.65   5.49 \t normalized + weighted:  -0.36   1.27  -0.10   1.95\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.06   7.33   5.36 \t normalized + weighted:  -0.41   1.13  -0.13   1.68\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.12   6.85   4.93 \t normalized + weighted:  -0.42   1.23  -0.21   1.69\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.49   4.72   4.98 \t normalized + weighted:  -0.30   1.66  -0.20   2.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.49   4.72   4.98 \t normalized + weighted:  -0.30   1.66  -0.20   2.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.62   4.69   5.29 \t normalized + weighted:   0.08   1.66  -0.14   2.53\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.91   4.72   5.66 \t normalized + weighted:   0.02   1.66  -0.07   2.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.20   5.10   6.33 \t normalized + weighted:  -0.04   1.58   0.07   2.75\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.74   5.09   5.88 \t normalized + weighted:   0.05   1.58  -0.02   2.60\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.66   5.01   5.74 \t normalized + weighted:   0.07   1.60  -0.05   2.58\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.66   5.01   5.73 \t normalized + weighted:   0.07   1.60  -0.05   2.58\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.86   5.16   6.08 \t normalized + weighted:   0.03   1.57   0.02   2.64\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.40  10.10   7.97 \t normalized + weighted:   0.12   0.58   0.39   1.62\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.40  10.10   7.97 \t normalized + weighted:   0.12   0.58   0.39   1.62\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.38  10.19   8.58 \t normalized + weighted:   0.12   0.56   0.52   1.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.43   7.50  10.17 \t normalized + weighted:  -0.49   1.10   0.83   3.22\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.21   6.98   7.70 \t normalized + weighted:   0.16   1.20   0.34   2.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.44   9.44   9.64 \t normalized + weighted:   0.11   0.71   0.73   2.40\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.83   9.48   9.59 \t normalized + weighted:   0.03   0.70   0.72   2.37\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.83   9.48   9.59 \t normalized + weighted:   0.03   0.70   0.72   2.37\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.07   9.17  11.15 \t normalized + weighted:  -0.01   0.77   1.03   2.99\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.27   9.34   9.56 \t normalized + weighted:   0.15   0.73   0.71   2.41\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.01   8.88  12.13 \t normalized + weighted:   0.40   0.82   1.23   3.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.49   9.37   9.58 \t normalized + weighted:   0.10   0.73   0.72   2.40\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.51   9.87   9.24 \t normalized + weighted:  -0.10   0.63   0.65   2.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.37  11.24   9.02 \t normalized + weighted:   0.13   0.35   0.60   1.59\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.82  11.43   9.17 \t normalized + weighted:   0.04   0.31   0.63   1.58\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.62  11.52   9.73 \t normalized + weighted:  -0.12   0.30   0.75   1.73\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.39  10.71   8.82 \t normalized + weighted:  -0.08   0.46   0.56   1.70\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.63  11.74   9.10 \t normalized + weighted:   0.07   0.25   0.62   1.45\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.81  11.52   9.11 \t normalized + weighted:   0.04   0.30   0.62   1.53\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.71  11.70   9.11 \t normalized + weighted:   0.06   0.26   0.62   1.47\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.31  13.20   9.29 \t normalized + weighted:   0.14  -0.04   0.66   1.03\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.31  13.20   9.29 \t normalized + weighted:   0.14  -0.04   0.66   1.03\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.31  15.32   7.41 \t normalized + weighted:   0.94  -0.46   0.28  -0.30\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU UCCCUGAUUAACGAGUGGAGUGAUGCGUUUUGAAGUUCGUUACAGUAGGAGGUUUCAACGGUUGGUGUGGGGAAAAUCGACACAUCAGCCUGUGGUUAGGCGUUGACUGCGCUUACCCAUGGUCAGAACAGAUGGAGUAGGAGCCUUACUAUGAGUAAAGGAGAAGAACUUUUCACU 1.6578910100613355\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.73  11.24   6.79 \t normalized + weighted:   0.45   0.35   0.16   0.85\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.73  11.24   6.79 \t normalized + weighted:   0.45   0.35   0.16   0.85\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.53  11.57   7.07 \t normalized + weighted:   0.49   0.29   0.21   0.83\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.56  11.56   7.10 \t normalized + weighted:   0.49   0.29   0.22   0.85\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.34  15.69  14.06 \t normalized + weighted:   0.33  -0.54   1.61   1.79\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.90   9.82   8.84 \t normalized + weighted:   0.62   0.64   0.57   2.00\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.13   8.31   6.86 \t normalized + weighted:   0.57   0.94   0.17   1.85\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.09   8.07   6.57 \t normalized + weighted:   0.58   0.99   0.11   1.83\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.96   7.95   7.35 \t normalized + weighted:   0.41   1.01   0.27   2.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.96   7.95   7.35 \t normalized + weighted:   0.41   1.01   0.27   2.13\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.47   7.46   7.35 \t normalized + weighted:   0.31   1.11   0.27   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.47   7.45   7.34 \t normalized + weighted:   0.31   1.11   0.27   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.49   6.56   6.46 \t normalized + weighted:   0.30   1.29   0.09   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.90   8.55   7.84 \t normalized + weighted:   0.42   0.89   0.37   2.10\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.26   6.80   6.44 \t normalized + weighted:   0.35   1.24   0.09   2.21\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.67   6.01   6.44 \t normalized + weighted:   0.47   1.40   0.09   2.48\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.76   6.49   6.40 \t normalized + weighted:   0.65   1.30   0.08   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.21   7.06   6.54 \t normalized + weighted:   0.56   1.19   0.11   2.16\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.09   6.59   6.18 \t normalized + weighted:   0.58   1.28   0.04   2.20\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.96   5.42   5.36 \t normalized + weighted:   0.41   1.52  -0.13   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.53   5.57   5.28 \t normalized + weighted:   0.29   1.49  -0.14   2.24\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.35   5.58   5.32 \t normalized + weighted:   0.13   1.48  -0.14   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.49   5.47   5.32 \t normalized + weighted:   0.10   1.51  -0.14   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.48   7.87   5.93 \t normalized + weighted:   0.50   1.03  -0.01   1.69\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.01   7.43   5.88 \t normalized + weighted:   0.40   1.11  -0.02   1.82\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.84   7.85   6.33 \t normalized + weighted:   0.43   1.03   0.07   1.83\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.84   7.85   6.33 \t normalized + weighted:   0.43   1.03   0.07   1.83\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.37   7.93   7.92 \t normalized + weighted:   0.13   1.01   0.38   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.37   7.93   7.92 \t normalized + weighted:   0.13   1.01   0.38   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.37   7.93   7.92 \t normalized + weighted:   0.13   1.01   0.38   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.88   8.17   7.92 \t normalized + weighted:  -0.18   0.97   0.38   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.91   8.17   7.92 \t normalized + weighted:  -0.18   0.97   0.38   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.41   5.79   7.92 \t normalized + weighted:  -0.08   1.44   0.38   3.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.90   8.17   7.92 \t normalized + weighted:  -0.18   0.97   0.38   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.90   8.17   7.92 \t normalized + weighted:  -0.18   0.97   0.38   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.53   7.97   7.93 \t normalized + weighted:  -0.31   1.01   0.39   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.53   7.97   7.93 \t normalized + weighted:  -0.31   1.01   0.39   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.53   7.97   7.93 \t normalized + weighted:  -0.31   1.01   0.39   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.53   7.39   7.35 \t normalized + weighted:  -0.31   1.12   0.27   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.53   7.39   7.35 \t normalized + weighted:  -0.31   1.12   0.27   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.52  10.23  10.17 \t normalized + weighted:  -0.30   0.55   0.83   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.50  11.70  11.65 \t normalized + weighted:  -0.30   0.26   1.13   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.00   9.17  10.61 \t normalized + weighted:  -0.20   0.77   0.92   2.82\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.56  11.28  11.20 \t normalized + weighted:  -0.31   0.34   1.04   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.75  10.61  10.75 \t normalized + weighted:  -0.35   0.48   0.95   2.38\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.08   7.66   6.46 \t normalized + weighted:  -0.02   1.07   0.09   1.93\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.03   8.27   7.97 \t normalized + weighted:  -0.21   0.95   0.39   2.23\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.03   8.27   7.97 \t normalized + weighted:  -0.21   0.95   0.39   2.24\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.49   8.00   8.89 \t normalized + weighted:  -0.30   1.00   0.58   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.48   8.00   8.88 \t normalized + weighted:  -0.30   1.00   0.58   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.48   7.99   8.83 \t normalized + weighted:  -0.30   1.00   0.57   2.61\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.49   8.00   8.89 \t normalized + weighted:  -0.30   1.00   0.58   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.05   7.52   7.85 \t normalized + weighted:  -0.21   1.10   0.37   2.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.69   7.87   7.63 \t normalized + weighted:  -0.14   1.03   0.33   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.38   9.53   6.55 \t normalized + weighted:   0.12   0.69   0.11   1.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.89   9.03   8.70 \t normalized + weighted:   0.02   0.79   0.54   2.22\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.45   9.51   6.62 \t normalized + weighted:   0.11   0.70   0.12   1.37\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.58   7.71   8.76 \t normalized + weighted:   0.28   1.06   0.55   2.68\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.41   9.52   6.59 \t normalized + weighted:   0.12   0.70   0.12   1.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.41   9.58   6.59 \t normalized + weighted:   0.12   0.68   0.12   1.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.81   9.22   6.86 \t normalized + weighted:  -0.16   0.76   0.17   1.55\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.18   8.63   6.92 \t normalized + weighted:  -0.24   0.87   0.18   1.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.40   8.81   8.33 \t normalized + weighted:  -0.28   0.84   0.47   2.17\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.18   8.63   6.92 \t normalized + weighted:  -0.24   0.87   0.18   1.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.20   6.63   7.57 \t normalized + weighted:  -0.84   1.27   0.31   2.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.20   6.63   7.57 \t normalized + weighted:  -0.84   1.27   0.31   2.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.10   6.09   7.02 \t normalized + weighted:  -0.82   1.38   0.20   2.64\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.01   7.97   8.81 \t normalized + weighted:  -0.80   1.01   0.56   2.61\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -18.76   7.87   8.81 \t normalized + weighted:  -1.15   1.03   0.56   2.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.21   7.85   9.31 \t normalized + weighted:  -0.84   1.03   0.66   2.82\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.58   8.20   8.96 \t normalized + weighted:  -0.92   0.96   0.59   2.59\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -17.23   8.55   8.96 \t normalized + weighted:  -0.85   0.89   0.59   2.47\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.92   8.96   9.52 \t normalized + weighted:  -0.58   0.81   0.70   2.52\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.56   9.42  11.08 \t normalized + weighted:  -0.71   0.72   1.02   2.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.55   9.41  11.06 \t normalized + weighted:  -0.71   0.72   1.01   2.88\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.14  10.83  11.21 \t normalized + weighted:  -0.63   0.43   1.04   2.46\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.85  10.76   9.79 \t normalized + weighted:  -0.37   0.45   0.76   2.01\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.74  12.86  11.98 \t normalized + weighted:  -0.35   0.03   1.20   2.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.74  12.53  11.72 \t normalized + weighted:  -0.35   0.09   1.14   2.06\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.84  12.56  11.74 \t normalized + weighted:  -0.37   0.09   1.15   2.06\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.11   9.44   7.74 \t normalized + weighted:  -0.42   0.71   0.35   1.77\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.80   8.57   9.47 \t normalized + weighted:  -0.36   0.89   0.69   2.63\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -16.26   9.73   9.81 \t normalized + weighted:  -0.65   0.65   0.76   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.00   8.83   7.74 \t normalized + weighted:   0.20   0.83   0.35   1.97\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.84   8.84   8.73 \t normalized + weighted:   0.23   0.83   0.55   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.46   8.85  10.94 \t normalized + weighted:   0.31   0.83   0.99   3.03\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.26   9.77  11.26 \t normalized + weighted:   0.35   0.65   1.05   2.83\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.46  12.29  11.18 \t normalized + weighted:   0.91   0.14   1.04   1.96\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.58  11.40  11.40 \t normalized + weighted:   0.68   0.32   1.08   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.56  11.45  11.34 \t normalized + weighted:   0.69   0.31   1.07   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.01  11.42  10.55 \t normalized + weighted:   0.40   0.32   0.91   2.04\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.88  10.78  10.86 \t normalized + weighted:   0.02   0.44   0.97   2.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.24  10.52  11.14 \t normalized + weighted:  -0.05   0.50   1.03   2.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.26   9.62  11.31 \t normalized + weighted:  -0.05   0.68   1.06   2.90\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.06   9.65  11.38 \t normalized + weighted:  -0.01   0.67   1.08   2.91\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.63   9.05  11.33 \t normalized + weighted:   0.07   0.79   1.07   3.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.51   8.30   9.97 \t normalized + weighted:   0.10   0.94   0.79   2.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.36   9.58   9.84 \t normalized + weighted:  -0.27   0.68   0.77   2.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.50   9.11   9.53 \t normalized + weighted:  -0.30   0.78   0.71   2.47\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.44   8.91   8.91 \t normalized + weighted:   0.31   0.82   0.58   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.44   8.87   8.87 \t normalized + weighted:   0.31   0.83   0.57   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.37   9.19   9.19 \t normalized + weighted:   0.33   0.76   0.64   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.26   7.19  10.28 \t normalized + weighted:  -0.05   1.16   0.86   3.36\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.33   9.01  10.28 \t normalized + weighted:  -0.27   0.80   0.86   2.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -15.13   8.60  10.28 \t normalized + weighted:  -0.43   0.88   0.86   2.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.97   8.60  10.93 \t normalized + weighted:  -0.39   0.88   0.99   3.11\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.22   8.73  10.93 \t normalized + weighted:  -0.04   0.85   0.99   3.06\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.49  10.37  10.92 \t normalized + weighted:  -0.10   0.53   0.98   2.52\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.49  10.36  10.93 \t normalized + weighted:  -0.10   0.53   0.99   2.52\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.45  11.12  11.56 \t normalized + weighted:  -0.09   0.38   1.11   2.48\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.68  10.21   9.48 \t normalized + weighted:   0.06   0.56   0.70   2.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.29   9.84  10.02 \t normalized + weighted:   0.34   0.63   0.80   2.39\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.00   9.83  10.00 \t normalized + weighted:   0.40   0.63   0.80   2.39\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.17   9.88  10.26 \t normalized + weighted:   0.37   0.62   0.85   2.46\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.79  10.18  10.89 \t normalized + weighted:   0.24   0.56   0.98   2.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.85  10.12  10.91 \t normalized + weighted:   0.43   0.58   0.98   2.60\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.43  10.18  10.34 \t normalized + weighted:   0.31   0.56   0.87   2.39\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.62   8.90  10.23 \t normalized + weighted:   0.28   0.82   0.85   2.78\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.55   8.95  10.08 \t normalized + weighted:   0.29   0.81   0.82   2.71\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.78   9.03   9.95 \t normalized + weighted:   0.24   0.79   0.79   2.64\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.98   9.11  10.15 \t normalized + weighted:   0.20   0.78   0.83   2.68\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.34   8.91   9.11 \t normalized + weighted:   0.13   0.82   0.62   2.40\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.86   8.65   8.31 \t normalized + weighted:   0.23   0.87   0.46   2.22\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.87   8.48   8.41 \t normalized + weighted:   0.23   0.90   0.48   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.59   8.97   8.00 \t normalized + weighted:   0.08   0.81   0.40   2.01\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.51  10.71   9.39 \t normalized + weighted:   0.30   0.46   0.68   1.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.47  11.01  11.58 \t normalized + weighted:   0.31   0.40   1.12   2.52\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.68  10.30   8.37 \t normalized + weighted:   0.26   0.54   0.47   1.69\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.06  10.54   9.35 \t normalized + weighted:  -0.01   0.49   0.67   1.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.86   9.93   9.94 \t normalized + weighted:   0.03   0.61   0.79   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.76  10.17  10.06 \t normalized + weighted:   0.05   0.57   0.81   2.30\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.35   9.44   7.46 \t normalized + weighted:  -0.07   0.71   0.29   1.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.38   9.21   7.06 \t normalized + weighted:  -0.08   0.76   0.21   1.62\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.40   9.33   7.04 \t normalized + weighted:  -0.08   0.73   0.21   1.57\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.27   9.41   7.07 \t normalized + weighted:  -0.05   0.72   0.21   1.55\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.84   9.61   7.14 \t normalized + weighted:   0.03   0.68   0.23   1.51\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.73   8.68   7.10 \t normalized + weighted:   0.05   0.86   0.22   1.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.37  10.24   7.10 \t normalized + weighted:   0.53   0.55   0.22   1.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.49  10.33   7.08 \t normalized + weighted:   0.50   0.53   0.22   1.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.98  10.55   7.04 \t normalized + weighted:   0.60   0.49   0.21   1.16\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.75  11.35   7.05 \t normalized + weighted:   0.65   0.33   0.21   0.90\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.19  16.38  16.32 \t normalized + weighted:   0.76  -0.68   2.06   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.19  16.39  16.15 \t normalized + weighted:   0.76  -0.68   2.03   2.25\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.19  14.48  15.86 \t normalized + weighted:   0.76  -0.30   1.97   2.79\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.60  13.29  10.54 \t normalized + weighted:   0.68  -0.06   0.91   1.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.91  12.10  10.54 \t normalized + weighted:   0.22   0.18   0.91   1.81\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.93  12.11  11.05 \t normalized + weighted:   0.21   0.18   1.01   1.98\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.11  12.66  12.38 \t normalized + weighted:   0.18   0.07   1.28   2.24\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.56  12.59  14.86 \t normalized + weighted:   0.29   0.08   1.77   3.09\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.47  13.03  11.03 \t normalized + weighted:   0.11  -0.01   1.01   1.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.89  12.98  11.50 \t normalized + weighted:   0.22   0.00   1.10   1.84\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.75  12.78  12.32 \t normalized + weighted:   0.25   0.04   1.26   2.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.87  14.26  13.32 \t normalized + weighted:   0.23  -0.25   1.46   2.02\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.58  13.28  14.95 \t normalized + weighted:   0.28  -0.06   1.79   2.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.58  13.46  15.14 \t normalized + weighted:   0.28  -0.09   1.83   2.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.59  12.55  14.23 \t normalized + weighted:   0.28   0.09   1.65   2.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.56  12.68  14.32 \t normalized + weighted:   0.29   0.06   1.66   2.88\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.61  12.31  14.00 \t normalized + weighted:   0.28   0.14   1.60   2.90\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.59  12.77  12.93 \t normalized + weighted:   0.28   0.05   1.39   2.39\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.63  12.45  13.14 \t normalized + weighted:   0.27   0.11   1.43   2.56\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.60  12.88  14.56 \t normalized + weighted:   0.28   0.02   1.71   2.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.59  14.78  17.51 \t normalized + weighted:   0.28  -0.36   2.30   3.24\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.46  13.85  17.78 \t normalized + weighted:   0.11  -0.17   2.36   3.64\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.29  14.51  17.78 \t normalized + weighted:   0.34  -0.30   2.36   3.42\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.37  14.52  12.85 \t normalized + weighted:   0.33  -0.30   1.37   1.78\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.47  13.58  12.89 \t normalized + weighted:   0.31  -0.12   1.38   2.10\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.20  13.98  18.14 \t normalized + weighted:   0.36  -0.20   2.43   3.72\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.93  12.65  12.61 \t normalized + weighted:   0.41   0.07   1.32   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.17  14.06  18.15 \t normalized + weighted:   0.37  -0.21   2.43   3.70\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.04  15.36  15.97 \t normalized + weighted:   0.19  -0.47   1.99   2.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.06  14.48  17.78 \t normalized + weighted:   0.39  -0.30   2.36   3.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.24  14.64  17.79 \t normalized + weighted:   0.35  -0.33   2.36   3.38\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.85  12.78  12.36 \t normalized + weighted:   0.23   0.04   1.27   2.19\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.86  14.50  14.36 \t normalized + weighted:   0.23  -0.30   1.67   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.81  12.19  11.49 \t normalized + weighted:   0.24   0.16   1.10   2.10\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.45  13.41  11.94 \t normalized + weighted:   0.31  -0.08   1.19   1.84\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.20  12.06  11.94 \t normalized + weighted:   0.36   0.19   1.19   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.67  12.77  12.07 \t normalized + weighted:   0.47   0.05   1.21   2.10\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -10.65  14.52  13.34 \t normalized + weighted:   0.47  -0.30   1.47   1.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.56  12.46  14.99 \t normalized + weighted:   0.09   0.11   1.80   3.18\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.03  14.24  14.99 \t normalized + weighted:  -0.21  -0.25   1.80   2.58\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.13  14.49  15.45 \t normalized + weighted:  -0.23  -0.30   1.89   2.65\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.59  13.44  14.05 \t normalized + weighted:  -0.32  -0.09   1.61   2.54\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.20  12.54  13.67 \t normalized + weighted:  -0.04   0.09   1.53   2.71\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.28  12.52  13.94 \t normalized + weighted:  -0.06   0.10   1.59   2.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.34  12.34  13.63 \t normalized + weighted:   0.13   0.13   1.53   2.76\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.30  12.29   9.68 \t normalized + weighted:  -0.06   0.14   0.74   1.46\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.71  11.76  10.32 \t normalized + weighted:  -0.14   0.25   0.86   1.85\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.18  14.69  14.29 \t normalized + weighted:  -0.04  -0.34   1.66   2.20\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -13.92  14.84  14.32 \t normalized + weighted:  -0.18  -0.37   1.66   2.16\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -14.99  14.72  15.16 \t normalized + weighted:  -0.40  -0.34   1.83   2.48\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -12.56  12.90  14.32 \t normalized + weighted:   0.09   0.02   1.66   2.80\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.54  12.76  13.05 \t normalized + weighted:   0.29   0.05   1.41   2.43\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]: -11.57  12.52  13.31 \t normalized + weighted:   0.29   0.10   1.46   2.60\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.76  11.16  10.11 \t normalized + weighted:   1.05   0.37   0.82   1.98\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.76  11.18  10.14 \t normalized + weighted:   1.05   0.36   0.83   1.99\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.72  11.16  10.02 \t normalized + weighted:   1.06   0.37   0.80   1.95\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.25   8.83   8.89 \t normalized + weighted:   0.95   0.83   0.58   2.35\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.27   8.06   9.11 \t normalized + weighted:   0.95   0.99   0.62   2.68\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.26   7.93   9.07 \t normalized + weighted:   0.95   1.01   0.61   2.71\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.49   8.10   9.11 \t normalized + weighted:   0.90   0.98   0.62   2.67\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.89   8.12   9.75 \t normalized + weighted:   0.82   0.98   0.75   2.87\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.85   8.73   9.64 \t normalized + weighted:   1.03   0.85   0.73   2.64\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.62   9.25   9.38 \t normalized + weighted:   1.28   0.75   0.68   2.38\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.84   9.59   8.87 \t normalized + weighted:   1.03   0.68   0.57   2.10\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.76   9.65   8.82 \t normalized + weighted:   1.05   0.67   0.56   2.06\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.75   9.56   8.74 \t normalized + weighted:   1.05   0.69   0.55   2.06\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.77   9.40   8.74 \t normalized + weighted:   1.05   0.72   0.55   2.11\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.98   8.94   8.82 \t normalized + weighted:   1.00   0.81   0.56   2.29\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -8.40   9.25   9.62 \t normalized + weighted:   0.92   0.75   0.72   2.46\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.69   8.45   8.37 \t normalized + weighted:   1.06   0.91   0.47   2.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.09   7.18  10.10 \t normalized + weighted:   1.18   1.16   0.82   3.31\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.48   8.37   8.37 \t normalized + weighted:   1.10   0.93   0.47   2.33\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.42   9.56   8.31 \t normalized + weighted:   1.12   0.69   0.46   1.92\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.36   9.45   8.11 \t normalized + weighted:   1.13   0.71   0.42   1.89\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.14   9.17   8.03 \t normalized + weighted:   1.17   0.77   0.41   1.95\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.20   9.13   8.06 \t normalized + weighted:   1.16   0.77   0.41   1.98\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:   8.72   9.16   9.17 \t normalized + weighted:   4.34   0.77   0.63   2.34\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.84   8.24   8.56 \t normalized + weighted:   1.03   0.95   0.51   2.44\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -9.47   8.33  10.05 \t normalized + weighted:   0.71   0.93   0.81   2.91\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.25   9.10   8.11 \t normalized + weighted:   1.15   0.78   0.42   2.00\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.13   9.09   7.95 \t normalized + weighted:   1.17   0.78   0.39   1.95\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.14   9.03   7.91 \t normalized + weighted:   1.17   0.79   0.38   1.96\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.23   8.89   7.71 \t normalized + weighted:   1.15   0.82   0.34   1.94\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -7.18   9.54   7.88 \t normalized + weighted:   1.16   0.69   0.38   1.78\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.62  10.06  10.02 \t normalized + weighted:   1.28   0.59   0.80   2.32\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.30   9.21  10.02 \t normalized + weighted:   1.34   0.76   0.80   2.60\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.19   8.60  10.06 \t normalized + weighted:   1.36   0.88   0.81   2.82\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  11.58   8.08   9.06 \t normalized + weighted:   4.92   0.98   0.61   2.66\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.80   7.53   9.15 \t normalized + weighted:   1.44   1.09   0.63   2.87\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -6.58   8.74   9.11 \t normalized + weighted:   1.28   0.85   0.62   2.46\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -5.79   9.33   9.18 \t normalized + weighted:   1.44   0.73   0.64   2.28\n",
      "energies[binding,dGfree,dGbound,(dGdiff)]:  -4.99   9.51   8.21 \t normalized + weighted:   1.60   0.70   0.44   1.90\n",
      "run time in s: 1243.6230192184448\n",
      "run time in min: 20.727050320307413\n"
     ]
    }
   ],
   "source": [
    "start = time.time()\n",
    "sRNA_design, mRNA_design, bestval_design = run_optimize(1, model_rri, cost_dG, optimize=sa_optimize, EI=-30, EM=-15, verbose=True, steps=1000)\n",
    "end = time.time()\n",
    "print(f'run time in s: {end - start}')\n",
    "print(f'run time in min: {(end - start)/60}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "684c5e25-617e-4293-a8d9-5f3650dd927d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best design\n",
      "sRNA: AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU\n",
      "mRNA: UCCCUGAUUAACGAGUGGAGUGAUGCGUUUUGAAGUUCGUUACAGUAGGAGGUUUCAACGGUUGGUGUGGGGAAAAUCGACACAUCAGCCUGUGGUUAGGCGUUGACUGCGCUUACCCAUGGUCAGAACAGAUGGAGUAGGAGCCUUACUAUGAGUAAAGGAGAAGAACUUUUCACU\n",
      "Cost: 1.6578910100613355\n",
      "25 55\n",
      "Binding energy:  -8.31.  RBS opening energy unbound  15.32, bound   7.41 kcal/mol\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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",
      "text/plain": [
       "<PIL.EpsImagePlugin.EpsImageFile image mode=RGB size=700x700>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/jpeg": 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      "image/png": 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",
      "text/plain": [
       "<PIL.EpsImagePlugin.EpsImageFile image mode=RGB size=700x700>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 911.111x711.111 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bestval_design = cost_dG(sRNA_design, mRNA_design)\n",
    "\n",
    "print(\"Best design\")\n",
    "print('sRNA:', sRNA_design)\n",
    "print('mRNA:', mRNA_design)\n",
    "print('Cost:', bestval_design)\n",
    "i, j, k, l, be = rri.RNAup(mRNA_design, sRNA_design)\n",
    "print(i, j)\n",
    "open = rri.dGopen(mRNA_design, (rri.PARAMS['SD_pos'], rri.PARAMS['SD_pos']+29))\n",
    "open_b = rri.dGopen(mRNA_design, (rri.PARAMS['SD_pos'], rri.PARAMS['SD_pos']+29), constraint=(i, j))\n",
    "print('Binding energy: {:6.2f}.  RBS opening energy unbound {:6.2f}, bound {:6.2f} kcal/mol'.format(be, open, open_b))\n",
    "\n",
    "mRNA_unbound, sRNA_unbound = rri.prediction_unbound(mRNA_design, sRNA_design)\n",
    "rri.draw_RNAplot_mRNA(mRNA_design, mRNA_unbound, output='unbound_thermodynamic_design.ps')\n",
    "mRNA_bound, sRNA_bound = rri.prediction_bound(mRNA_design, sRNA_design)\n",
    "rri.draw_RNAplot(sRNA_design, mRNA_design, sRNA_bound, mRNA_bound, output='bound_thermodynamic_design.ps')\n",
    "\n",
    "rri.plot_energylandscape(sRNA_design, mRNA_design, id1='DsrA', id2=\"designed mRNA\", figure_path=\"thermodynamic_design_landscape.pdf\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bd5da9e-7d1d-4647-957f-be4038a2deb8",
   "metadata": {},
   "source": [
    "## Extending the cost function to kinetic features\n",
    "\n",
    "In addition to the terms in the previouse cost function, we include\n",
    "- a low free energy of the barrier state along the best folding path and\n",
    "- and a stable seed interaction as start of the best folding path\n",
    "\n",
    "The targeted energies are provided through the following agruments:\n",
    "- binding energy: t_bind=-13 (in kcal/mol; maximum)\n",
    "- opening energy of the RBS in the bound state: t_dG_bound=6 (in kcal/mol; maximum)\n",
    "- opening energy of the RBS in the unbound mRNA: t_dG_free=11 (in kcal/mol; minimum)\n",
    "- additional optimization weight on the difference between the bound and free RNS opening energy: target_t_dG_diff=True, \n",
    "- free (binding) energy of the barrier state: t_barrier=-1 (in kcal/mol; maximum)\n",
    "- free energy of the seed interaction: t_seed=-1 (in kcal/mol; maximum)\n",
    "  \n",
    "Good designs are usually reaches within 1000 iterations (<10min on current laptop cpu), but shorter runs can alread get close to the targeted feature values. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5a448409-bb97-41ec-8f10-9118ac3ebf71",
   "metadata": {},
   "outputs": [],
   "source": [
    "def cost_kinetics(\n",
    "    sRNA,\n",
    "    mRNA,\n",
    "    region=(rri.PARAMS[\"SD_pos\"], rri.PARAMS[\"SD_pos\"] + 29),\n",
    "    t_bind=-13,\n",
    "    t_dG_bound=6,\n",
    "    t_dG_free=11,\n",
    "    target_t_dG_diff=True, \n",
    "    t_barrier=-1,\n",
    "    t_seed=-1,\n",
    "    verbose=False,\n",
    "    vverbose=False,\n",
    "):\n",
    "    # predict best interaction structure\n",
    "    intarna_args = (\n",
    "        rri.gen_intarna_args()\n",
    "    )  # + [ '--qRegion', f'1-{rri.PARAMS[\"SD_pos\"]}']\n",
    "    df = rri.run_intarna(\n",
    "        sRNA, mRNA, id1=\"sRNA\", id2=\"mRNA\", temperature=37.0, intarna_args=intarna_args\n",
    "    )\n",
    "    mfe_interaction = df.to_dict(orient=\"records\")[0]\n",
    "\n",
    "    # compute kinetic features of best interaction structure\n",
    "    bp_list = rri.intarna_to_bplist(mfe_interaction[\"bpList\"], zero_based=True)\n",
    "    max_j = max([bp[1] for bp in bp_list])\n",
    "    \n",
    "    if not max_j < region[0]:\n",
    "        return 99\n",
    "    seed_length = 5\n",
    "    if len(bp_list) < seed_length:\n",
    "        return 99\n",
    "\n",
    "    \n",
    "    el = rri.EnergyLandscape(sRNA, mRNA, bp_list)\n",
    "    min_barrier_energies = el.get_min_barrier_Es(seed_length)\n",
    "    seed_stabilities = el.get_seed_Es(seed_length)\n",
    "\n",
    "    min_barrier = min(min_barrier_energies)\n",
    "    seed_stability_min_barrier = seed_stabilities[\n",
    "        min_barrier_energies.index(min_barrier)\n",
    "    ]\n",
    "    rrikindp_full_E = el.get_full_E() # from RRIkinDP\n",
    "    interactionE = mfe_interaction[\"E\"] # from IntaRNA\n",
    "\n",
    "    # compute opening energies for RBS in unbound state:\n",
    "    open_free = rri.dGopen(mRNA, region)\n",
    "    \n",
    "    # compute opening energies for RBS in unbound state:\n",
    "    open_bound = rri.dGopen(\n",
    "        mRNA, region, [int(mfe_interaction[\"start2\"]), int(mfe_interaction[\"end2\"])]\n",
    "    )\n",
    "\n",
    "    # difference between targeted opening energies\n",
    "    t_dG_diff=t_dG_bound-t_dG_free\n",
    "\n",
    "\n",
    "    # weight features in cost function\n",
    "    bind, dG_bound, dG_free, dG_diff, seed, barrier = (\n",
    "        (rrikindp_full_E  - t_bind) / 3,\n",
    "        (open_bound - t_dG_bound) / 1,\n",
    "        (t_dG_free-open_free) / 1,\n",
    "        2*(open_bound - open_free - t_dG_diff) , \n",
    "        (seed_stability_min_barrier - t_seed) / 3,\n",
    "        (min_barrier - t_barrier) / 1,\n",
    "    )\n",
    "\n",
    "\n",
    "    # compute cost\n",
    "    if target_t_dG_diff:\n",
    "        cost = LogSumExp(bind, dG_bound, dG_free, seed, barrier)\n",
    "    else:\n",
    "        cost = LogSumExp(bind, dG_bound, dG_free, dG_diff, seed, barrier)\n",
    "\n",
    "    # output features\n",
    "    if verbose:\n",
    "        print(\"========================next design==================================\")\n",
    "        print(\"bind, dG_bound, dG_free, dG_diff, seed, barrier\")\n",
    "        print(\n",
    "            \"{:6.2f} {:6.2f} {:6.2f} {:6.2f} {:6.2f} {:6.2f} {}\".format(\n",
    "               bind, dG_bound, dG_free, dG_diff, seed, barrier, 'weighted difference from target energies'\n",
    "            )\n",
    "        )\n",
    "        print(\n",
    "            \"{:6.2f} {:6.2f} {:6.2f} {:6.2f} {:6.2f} {:6.2f} {}\".format(\n",
    "                rrikindp_full_E,\n",
    "                open_bound,\n",
    "                open_free,\n",
    "                open_bound - open_free,\n",
    "                seed_stability_min_barrier,\n",
    "                min_barrier,\n",
    "                'energies'\n",
    "            )\n",
    "        )\n",
    "        print(f'cost score: {cost}')\n",
    "    if vverbose:\n",
    "        print(\"designed mRNA\")\n",
    "        print(mRNA)\n",
    "        \n",
    "        print(f\"The overall cost score is {cost}, it is computed from the following features (target energies in brackets):\")\n",
    "        print(f\"- free energy of the full interaction: {rrikindp_full_E} kcal/mol ({t_bind} kcal/mol)\")\n",
    "        print(f\"- free energy of the barrier state: {min_barrier} kcal/mol ({t_barrier} kcal/mol)\")\n",
    "        print(f\"- free energy of {seed_length}bps seed from which the minimum barrier folding paths starts: {seed_stability_min_barrier} kcal/mol ({t_seed} kcal/mol)\")\n",
    "        print(f\"- seed resulting in the minimum barrier state folding path starts at base pair {min_barrier_energies.index(min_barrier)+1}\")\n",
    "        print(f\"- opening energy of the RBS+30nts when sRNA is bound: {open_bound} kcal/mol ({t_dG_bound} kcal/mol)\")\n",
    "        print(f\"- opening energy of the RBS+30nts when mRNA is free: {open_free} kcal/mol ({t_dG_free} kcal/mol)\")\n",
    "        print(f\"- change of the opening energy of the RBS+30nts when sRNA binds: {open_bound - open_free} kcal/mol ({t_dG_diff} kcal/mol; currently not targeted)\")\n",
    "\n",
    "        print('')\n",
    "        print(f\"IntaRNA results:\")\n",
    "        print(f\"The interaction range on the sRNA is {mfe_interaction['start1']}-{mfe_interaction['end1']}\")\n",
    "        print(f\"The interaction range on the mRNA is {mfe_interaction['start2']}-{mfe_interaction['end2']}\")\n",
    "        print(f\"Base pair list: {mfe_interaction['bpList']}\")\n",
    "        #print(f'interaction in db notation: {mfe_interaction[\"hybridDPfull\"]}')\n",
    "        print(f'E: {mfe_interaction[\"E\"]}, ED1: {mfe_interaction[\"ED1\"]}, ED2: {mfe_interaction[\"ED2\"]}, E_loops: {mfe_interaction[\"E_loops\"]}')\n",
    "        '''\n",
    "        print('')\n",
    "        print('dG_open based on interaction prediction from RNAup:')\n",
    "        print(f\"RBS acessibility:\\n free mRNA:{open_free}; bound:{open_bound }; difference:{open_bound - open_free}\")\n",
    "        i, j, k, l, be = rri.RNAup(mRNA, sRNA)\n",
    "        print(\"RNAup prediction for comparision\")\n",
    "        print(\"Binding region of rpos:\", (i, j))\n",
    "        print(\"Binding region of rdsa:\", (k, l))\n",
    "        print(\"Binding Energy:\", be, \"kcal/mol\")\n",
    "        '''\n",
    "    return cost"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0139b9c6-7033-4075-b741-26e28c0d79ef",
   "metadata": {},
   "source": [
    "### Generate design with kinetic cost function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "15c58e88-fa2e-4f72-95b6-9ee5fd2f3e5a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GUCUCGUUUGUAUGCCUUCUCGCUGUGUUUGGAAGUUUGUUGCGAUAGGGAGUCUUUUGUAUCGUUAGAUUUGUUCGUACAGCAAAGGGGCCAAUUAACCUCAGAAAUUCCAUGCUGUGACUGCUGGAUCAGAGAGGCAGGAGCCAUGUCAUGAGUAAAGGAGAAGAACUUUUCACU 5.464694481511163\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.34   2.66   3.72  12.76   1.36   5.14 weighted difference from target energies\n",
      " -5.98   8.66   7.28   1.38   3.09   4.14 energies\n",
      "cost score: 5.483529647652122\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.70   4.02   0.30   8.64   1.36   5.14 weighted difference from target energies\n",
      " -4.90  10.02  10.70  -0.68   3.09   4.14 energies\n",
      "cost score: 5.506655390453058\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.20   4.07   0.46   9.04  -0.08   1.62 weighted difference from target energies\n",
      " -6.40  10.07  10.54  -0.48  -1.25   0.62 energies\n",
      "cost score: 4.316049088195889\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GUCUCGUUUGUAUGCCUUCUCGCUGUGUUUGGAAGUUUGUUGCGAUAGGGAGUCUUUUGUAGCGUUAGAUUUGUUCGUACAGCAAAGGGGCCAAUUAACCCCAGAAAUUCCAUGCUGUGACUGCUUGUUCAGAGAGGCAGGAGCCAUGUCAUGAGUAAAGGAGAAGAACUUUUCACU 4.316049088195889\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.38   4.19   2.75  13.89   0.12   1.60 weighted difference from target energies\n",
      " -8.86  10.19   8.25   1.94  -0.63   0.60 energies\n",
      "cost score: 4.520390849481678\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.35   3.72   1.40  10.23   0.00   1.24 weighted difference from target energies\n",
      " -8.94   9.72   9.60   0.11  -0.99   0.24 energies\n",
      "cost score: 3.9815788990339245\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GUCUCGUUUGUAUGCCUUCUCGCUGUGUUUGGAAGUUUGUUGCGAUAGGGAGUCUUUUGUAGUGUUAGAUUUGUUCGUACAGCAAAGGGGCCAAUUAACCCCAGAAAUUCCAUGCUCUGACUGCUUAUUCAGAGAGGCAGGAGCCAUGUCAUGAGUAAAGGAGAAGAACUUUUCACU 3.9815788990339245\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.38   4.80   0.65  10.89  -0.02   1.19 weighted difference from target energies\n",
      " -8.86  10.80  10.35   0.45  -1.05   0.19 energies\n",
      "cost score: 4.881002691996237\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.34   4.88   0.58  10.91  -0.06   1.06 weighted difference from target energies\n",
      " -8.98  10.88  10.42   0.45  -1.17   0.06 energies\n",
      "cost score: 4.948189103090325\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.79   6.13   0.29  12.85  -0.03   1.15 weighted difference from target energies\n",
      " -7.64  12.13  10.71   1.43  -1.09   0.15 energies\n",
      "cost score: 6.158584012213854\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.36   4.71   0.70  10.82  -0.02   1.18 weighted difference from target energies\n",
      " -8.92  10.71  10.30   0.41  -1.06   0.18 energies\n",
      "cost score: 4.797475630990911\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.36   4.31   0.94  10.50  -0.01   1.22 weighted difference from target energies\n",
      " -8.93  10.31  10.06   0.25  -1.02   0.22 energies\n",
      "cost score: 4.446179021662635\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.58   9.02   1.06  20.17  -0.63  -1.89 weighted difference from target energies\n",
      " -5.26  15.02   9.94   5.08  -2.89  -2.89 energies\n",
      "cost score: 9.022606023226558\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.35   3.88   1.37  10.49   0.06   1.43 weighted difference from target energies\n",
      " -8.94   9.88   9.63   0.25  -0.81   0.43 energies\n",
      "cost score: 4.1189611844817735\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.33   7.00  -0.99  12.02   0.39   2.41 weighted difference from target energies\n",
      " -9.02  13.00  11.99   1.01   0.16   1.41 energies\n",
      "cost score: 7.016309254233997\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.35   4.19   1.19  10.76   1.27   4.98 weighted difference from target energies\n",
      " -5.95  10.19   9.81   0.38   2.82   3.98 energies\n",
      "cost score: 5.433952821520966\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.92   4.18   1.20  10.75   0.36   1.52 weighted difference from target energies\n",
      "-10.24  10.18   9.80   0.38   0.09   0.52 energies\n",
      "cost score: 4.34525690537564\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.92   4.08   1.53  11.20   0.36   1.51 weighted difference from target energies\n",
      "-10.23  10.08   9.47   0.60   0.09   0.51 energies\n",
      "cost score: 4.275872424592983\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.09   4.06   1.52  11.16   0.42   3.54 weighted difference from target energies\n",
      " -9.73  10.06   9.48   0.58   0.26   2.54 energies\n",
      "cost score: 4.6190382696200825\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.92   3.94   1.52  10.93   0.37   1.52 weighted difference from target energies\n",
      "-10.23   9.94   9.48   0.47   0.10   0.52 energies\n",
      "cost score: 4.168002375893096\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.25   2.93   2.21  10.29   0.39   1.51 weighted difference from target energies\n",
      " -9.26   8.93   8.79   0.14   0.16   0.51 energies\n",
      "cost score: 3.6218727872471104\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GUCUCGUUUCUAUGCCUUCCCGCUGUGUUUGGAAGUUUGUUGCGAUAGGGAGUCUUUUGUAGUGUUAGUUUUGUUCGUGCAGCAAAGGGGCCAAGUAACCCCAGAAAUUCCAUGCUCUGACUACGUAUUCAGAGAGGCAGGAGCCAUGUCAUGAGUAAAGGAGAAGAACUUUUCACU 3.6218727872471104\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.07   2.23   2.39   9.25   0.39   1.59 weighted difference from target energies\n",
      " -9.78   8.23   8.61  -0.38   0.16   0.59 energies\n",
      "cost score: 3.3865724136036173\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GUCUCGUUUCUAUGCCUUCCCGCUGUGUUUGGAAGUUUGUUGCGAUAGGGAGUCUUUUGUAGUGUUAGUUUUGUUCGUGCAGCAAAGGGGCAAAGUAACCCCAGAAAUUCCAUGCUCUGACUACGUAUUCAGAGAGGCAGGAGCCAUGUCAUGAGUAAAGGAGAAGAACUUUUCACU 3.3865724136036173\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.72   4.90   1.63  13.06   0.27   1.88 weighted difference from target energies\n",
      "-10.84  10.90   9.37   1.53  -0.18   0.88 energies\n",
      "cost score: 5.0034186608902855\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.57   1.65   3.07   9.44   0.15   2.05 weighted difference from target energies\n",
      "-11.29   7.65   7.93  -0.28  -0.55   1.05 energies\n",
      "cost score: 3.621896086113873\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.32   2.67   4.01  13.36   0.30   2.43 weighted difference from target energies\n",
      " -9.03   8.67   6.99   1.68  -0.09   1.43 energies\n",
      "cost score: 4.4573518310538525\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.81  -0.27   5.85  11.17   0.37   2.60 weighted difference from target energies\n",
      "-10.58   5.73   5.15   0.58   0.11   1.60 energies\n",
      "cost score: 5.902564087582462\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.79   2.75   4.16  13.81  -0.05   3.19 weighted difference from target energies\n",
      " -7.64   8.75   6.84   1.91  -1.15   2.19 energies\n",
      "cost score: 4.7067212741169895\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.85   4.82   0.51  10.66  -0.08   2.94 weighted difference from target energies\n",
      " -7.46  10.82  10.49   0.33  -1.24   1.94 energies\n",
      "cost score: 5.025616189114635\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.64   4.96   0.02   9.97   0.53   5.38 weighted difference from target energies\n",
      " -5.08  10.96  10.98  -0.02   0.58   4.38 energies\n",
      "cost score: 5.930159866893218\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.65   4.85   0.01   9.72   0.53   5.36 weighted difference from target energies\n",
      " -5.06  10.85  10.99  -0.14   0.58   4.36 energies\n",
      "cost score: 5.877639280051202\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.65   4.97   0.01   9.96   0.53   5.36 weighted difference from target energies\n",
      " -5.04  10.97  10.99  -0.02   0.58   4.36 energies\n",
      "cost score: 5.921617055957666\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.91   4.94   0.03   9.94   1.33   4.46 weighted difference from target energies\n",
      " -7.26  10.94  10.97  -0.03   2.98   3.46 energies\n",
      "cost score: 5.468715365932865\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.83   4.91   0.06   9.94   1.27   4.22 weighted difference from target energies\n",
      " -7.52  10.91  10.94  -0.03   2.80   3.22 energies\n",
      "cost score: 5.36641619801075\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.50   4.85   0.18  10.07   0.88   3.11 weighted difference from target energies\n",
      " -8.51  10.85  10.82   0.04   1.64   2.11 energies\n",
      "cost score: 5.065422831654254\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.45   4.98  -0.25   9.44   0.88   3.09 weighted difference from target energies\n",
      " -8.64  10.98  11.25  -0.28   1.64   2.09 energies\n",
      "cost score: 5.160518007142889\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.47   4.95  -0.20   9.51   0.89   3.11 weighted difference from target energies\n",
      " -8.59  10.95  11.20  -0.24   1.67   2.11 energies\n",
      "cost score: 5.145556005114758\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.84   4.47   0.76  10.47   1.33   4.87 weighted difference from target energies\n",
      " -7.49  10.47  10.24   0.24   2.98   3.87 energies\n",
      "cost score: 5.43931823570046\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.65   5.07   0.39  10.91   1.36   4.20 weighted difference from target energies\n",
      " -8.04  11.07  10.61   0.46   3.08   3.20 energies\n",
      "cost score: 5.462983878685147\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.86   5.16   1.37  13.05   1.23   4.88 weighted difference from target energies\n",
      " -7.43  11.16   9.63   1.53   2.68   3.88 energies\n",
      "cost score: 5.766100060679976\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.01   3.62   1.64  10.52   1.22   4.79 weighted difference from target energies\n",
      " -6.97   9.62   9.36   0.26   2.67   3.79 energies\n",
      "cost score: 5.1565449641069225\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.62   3.62   1.73  10.70   0.70   3.31 weighted difference from target energies\n",
      " -5.13   9.62   9.27   0.35   1.09   2.31 energies\n",
      "cost score: 4.455109396282844\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.15   7.55  -1.26  12.57   0.57   3.48 weighted difference from target energies\n",
      " -6.55  13.55  12.26   1.29   0.71   2.48 energies\n",
      "cost score: 7.569387106950284\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.71   3.39   1.62  10.03   0.74   3.44 weighted difference from target energies\n",
      " -4.86   9.39   9.38   0.01   1.21   2.44 energies\n",
      "cost score: 4.420007700372998\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  3.12   3.35   0.36   7.41   0.88   4.07 weighted difference from target energies\n",
      " -3.64   9.35  10.64  -1.30   1.64   3.07 energies\n",
      "cost score: 4.7311469673362385\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.56   3.23   1.56   9.58   0.67   3.18 weighted difference from target energies\n",
      " -5.33   9.23   9.44  -0.21   1.01   2.18 energies\n",
      "cost score: 4.232959125458434\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.48   4.65   1.07  11.42   1.29   5.14 weighted difference from target energies\n",
      " -5.56  10.65   9.93   0.71   2.88   4.14 energies\n",
      "cost score: 5.681156852561191\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.09   3.49   1.25   9.48   0.86   3.25 weighted difference from target energies\n",
      " -9.73   9.49   9.75  -0.26   1.57   2.25 energies\n",
      "cost score: 4.210129339625366\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.76   3.49   0.49   7.96   0.94   3.40 weighted difference from target energies\n",
      " -7.72   9.49  10.51  -1.02   1.81   2.40 energies\n",
      "cost score: 4.2863898984227164\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.53   6.98   0.92  15.79   0.75   2.47 weighted difference from target energies\n",
      " -8.40  12.98  10.08   2.90   1.26   1.47 energies\n",
      "cost score: 6.995852668984492\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.03   3.50  -0.19   6.63   1.00   4.22 weighted difference from target energies\n",
      " -6.92   9.50  11.19  -1.69   1.99   3.22 energies\n",
      "cost score: 4.722090845054622\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.65   5.69   0.13  11.64   0.70   2.31 weighted difference from target energies\n",
      " -8.06  11.69  10.87   0.82   1.11   1.31 energies\n",
      "cost score: 5.745886107436904\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.33   4.70  -1.19   7.02   0.20   1.74 weighted difference from target energies\n",
      " -6.02  10.70  12.19  -1.49  -0.39   0.74 energies\n",
      "cost score: 4.851543436655757\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.31   2.08   0.90   5.96   0.20   1.68 weighted difference from target energies\n",
      " -6.06   8.08  10.10  -2.02  -0.41   0.68 energies\n",
      "cost score: 3.3020302925341594\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GUCUUGAUUCUAUGCCUUCCCGCUGUGCUUGGAGGUUUGUUGUGAUAGGGAGUCUUUAGUCGUGAGAGUUUGGUUCGUGUAACAACAGCAAAGAGAAACCACAGAAAUUCCAUGCUCUGACUAGGUAUGCAGAGAGGCAGGAGCCAUGUCAUGAGUAAAGGAGAAGAACUUUUCACU 3.3020302925341594\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.22   1.78   1.20   5.95   0.20   1.34 weighted difference from target energies\n",
      " -6.35   7.78   9.80  -2.02  -0.39   0.34 energies\n",
      "cost score: 3.15526170992395\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GUCUUGAUUCUAUGCCUUCCCGCUGUGCUUGGAGGUUUGUUGUGAUAGGGAGUCUUUAGUCGUGAGAGUUUGGUUCGUGUAACAACAGCGAAGAGAAACCACAGAAAUUCCAUGCUCUGACUAGGUAUGCAGAGAGGCAGGAGCCAUGUCAUGAGUAAAGGAGAAGAACUUUUCACU 3.15526170992395\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.96   1.75   1.75   6.98   0.80   3.20 weighted difference from target energies\n",
      " -7.13   7.75   9.25  -1.51   1.40   2.20 energies\n",
      "cost score: 3.813230802212211\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.76   2.30   0.71   6.01  -0.02   0.05 weighted difference from target energies\n",
      " -7.73   8.30  10.29  -1.99  -1.05  -0.95 energies\n",
      "cost score: 2.987693242441998\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU GUCUUGAUUCUAUGCCCUCCCGCUGUGCUUGGAGGUUUGUUGUGAUAGGGAGUCUUUAGUCGUGAGAGUUUGGUUCGUGUAACAACAGCGAAGAGAAACCACAGAAAUUCCAUGCUCUGACUAGGUAUGCAGAGAGGCAGGAGCCAUGUCAUGAGUAAAGGAGAAGAACUUUUCACU 2.987693242441998\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.71   3.38   0.12   7.00  -0.02  -0.05 weighted difference from target energies\n",
      " -7.88   9.38  10.88  -1.50  -1.05  -1.05 energies\n",
      "cost score: 3.6343093199788443\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.80   2.55   0.34   5.78  -0.01   0.17 weighted difference from target energies\n",
      " -7.61   8.55  10.66  -2.11  -1.04  -0.83 energies\n",
      "cost score: 3.1083547988396\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.72   2.50   0.69   6.39  -0.02  -0.05 weighted difference from target energies\n",
      " -7.85   8.50  10.31  -1.80  -1.05  -1.05 energies\n",
      "cost score: 3.0776212133939174\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.69   6.48  -1.35  10.26  -0.02  -0.06 weighted difference from target energies\n",
      " -7.93  12.48  12.35   0.13  -1.06  -1.06 energies\n",
      "cost score: 6.48985140781867\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.30   5.78   1.02  13.61   0.09   0.27 weighted difference from target energies\n",
      " -9.09  11.78   9.98   1.81  -0.73  -0.73 energies\n",
      "cost score: 5.8099585093547645\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.14   3.19   0.09   6.57   0.18   1.18 weighted difference from target energies\n",
      " -6.59   9.19  10.91  -1.71  -0.47   0.18 energies\n",
      "cost score: 3.6475578319456585\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.26   3.07   0.03   6.20   0.16   1.54 weighted difference from target energies\n",
      " -6.23   9.07  10.97  -1.90  -0.51   0.54 energies\n",
      "cost score: 3.637145727772287\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.19   3.85  -0.28   7.14   0.07   1.35 weighted difference from target energies\n",
      " -6.43   9.85  11.28  -1.43  -0.80   0.35 energies\n",
      "cost score: 4.122453035562932\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.22   4.64  -0.02   9.24  -1.01  -3.02 weighted difference from target energies\n",
      " -6.34  10.64  11.02  -0.38  -4.02  -4.02 energies\n",
      "cost score: 4.7365004423643375\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.20   2.67   0.04   5.41   0.36   3.00 weighted difference from target energies\n",
      " -6.40   8.67  10.96  -2.29   0.08   2.00 energies\n",
      "cost score: 3.8289424897741346\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.69   4.69   0.77  10.92   0.52   2.42 weighted difference from target energies\n",
      " -7.94  10.69  10.23   0.46   0.57   1.42 energies\n",
      "cost score: 4.866108486275492\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.75   4.76   0.86  11.24   0.56   2.50 weighted difference from target energies\n",
      " -7.75  10.76  10.14   0.62   0.67   1.50 energies\n",
      "cost score: 4.934311383549643\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.44   4.76   2.40  14.32   0.36   1.08 weighted difference from target energies\n",
      "-11.69  10.76   8.60   2.16   0.08   0.08 energies\n",
      "cost score: 4.896843459282299\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.49   5.11   2.64  15.49   0.68   2.04 weighted difference from target energies\n",
      "-11.53  11.11   8.36   2.74   1.04   1.04 energies\n",
      "cost score: 5.247998220128847\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.30   4.98   0.51  10.98   0.57   1.70 weighted difference from target energies\n",
      "-12.10  10.98  10.49   0.49   0.70   0.70 energies\n",
      "cost score: 5.0492435825900275\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.35   4.78   0.65  10.84   0.49   1.46 weighted difference from target energies\n",
      "-11.94  10.78  10.35   0.42   0.46   0.46 energies\n",
      "cost score: 4.851649882643091\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.09   5.88   0.36  12.49   0.55   1.64 weighted difference from target energies\n",
      "-12.74  11.88  10.64   1.25   0.64   0.64 energies\n",
      "cost score: 5.908299305752713\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.32   5.65   0.06  11.42   0.58   1.74 weighted difference from target energies\n",
      "-12.04  11.65  10.94   0.71   0.74   0.74 energies\n",
      "cost score: 5.684309886530158\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.22   3.68   0.43   8.21   0.37   1.12 weighted difference from target energies\n",
      "-12.33   9.68  10.57  -0.90   0.12   0.12 energies\n",
      "cost score: 3.846483962334652\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.92   1.55   0.07   3.25   1.03   3.08 weighted difference from target energies\n",
      "-10.25   7.55  10.93  -3.38   2.08   2.08 energies\n",
      "cost score: 3.4917628808185124\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.83   1.55   0.07   3.23   1.05   3.14 weighted difference from target energies\n",
      "-10.52   7.55  10.93  -3.38   2.14   2.14 energies\n",
      "cost score: 3.526985698771656\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.48   3.00   0.34   6.69   1.51   4.53 weighted difference from target energies\n",
      " -8.56   9.00  10.66  -1.65   3.53   3.53 energies\n",
      "cost score: 4.813975062385898\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.98   1.41  -0.04   2.73   1.24   3.71 weighted difference from target energies\n",
      "-10.05   7.41  11.04  -3.63   2.71   2.71 energies\n",
      "cost score: 3.9517304139488285\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.38   1.41  -0.01   2.79   1.01   3.04 weighted difference from target energies\n",
      " -8.86   7.41  11.01  -3.60   2.04   2.04 energies\n",
      "cost score: 3.487880184980954\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.30   1.87   0.03   3.79   0.88   2.64 weighted difference from target energies\n",
      " -9.11   7.87  10.97  -3.10   1.64   1.64 energies\n",
      "cost score: 3.3180860512352623\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.23   1.76   0.57   4.67   1.12   3.35 weighted difference from target energies\n",
      " -9.30   7.76  10.43  -2.67   2.35   2.35 energies\n",
      "cost score: 3.751603409974125\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.21   1.91   0.59   4.99   1.08   3.25 weighted difference from target energies\n",
      " -9.38   7.91  10.41  -2.51   2.25   2.25 energies\n",
      "cost score: 3.7042537630536865\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.04   1.91   0.62   5.06   1.28   3.85 weighted difference from target energies\n",
      " -6.88   7.91  10.38  -2.47   2.85   2.85 energies\n",
      "cost score: 4.203364622454168\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.41   5.26  -0.87   8.78   1.51   4.52 weighted difference from target energies\n",
      " -5.76  11.26  11.87  -0.61   3.52   3.52 energies\n",
      "cost score: 5.707345712845664\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.17   3.89  -0.80   6.17   1.16   3.48 weighted difference from target energies\n",
      " -6.49   9.89  11.80  -1.91   2.48   2.48 energies\n",
      "cost score: 4.538379872112488\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.00   5.18  -0.44   9.48   1.07   3.20 weighted difference from target energies\n",
      " -6.99  11.18  11.44  -0.26   2.20   2.20 energies\n",
      "cost score: 5.36363172161475\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.15   4.65  -0.85   7.61   1.01   3.03 weighted difference from target energies\n",
      " -6.54  10.65  11.85  -1.20   2.03   2.03 energies\n",
      "cost score: 4.922464038669931\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.16   5.99  -0.98  10.01  -1.04  -3.13 weighted difference from target energies\n",
      " -6.53  11.99  11.98   0.00  -4.13  -4.13 energies\n",
      "cost score: 6.009618907214252\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.84   4.98   0.54  11.02   0.75   2.24 weighted difference from target energies\n",
      " -7.49  10.98  10.46   0.51   1.24   1.24 energies\n",
      "cost score: 5.102376033095334\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.10   6.15  -0.78  10.74   1.11   3.39 weighted difference from target energies\n",
      " -9.70  12.15  11.78   0.37   2.33   2.39 energies\n",
      "cost score: 6.220548796860248\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.14   6.09  -0.84  10.50   0.57   1.94 weighted difference from target energies\n",
      " -9.58  12.09  11.84   0.25   0.70   0.94 energies\n",
      "cost score: 6.117738322697397\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.06   5.80  -0.84   9.93   1.15   4.57 weighted difference from target energies\n",
      " -6.83  11.80  11.84  -0.04   2.46   3.57 energies\n",
      "cost score: 6.083023914952485\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.84   5.94  -0.84  10.20   1.16   3.73 weighted difference from target energies\n",
      " -7.47  11.94  11.84   0.10   2.48   2.73 energies\n",
      "cost score: 6.066026640925239\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.41   6.05  -0.83  10.43   0.81   2.44 weighted difference from target energies\n",
      " -8.76  12.05  11.83   0.21   1.44   1.44 energies\n",
      "cost score: 6.09126213342169\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.44   7.36  -2.21  10.29   1.13   3.53 weighted difference from target energies\n",
      " -8.68  13.36  13.21   0.15   2.38   2.53 energies\n",
      "cost score: 7.381751750808949\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.74   7.16  -3.20   7.91   0.64   2.91 weighted difference from target energies\n",
      " -7.78  13.16  14.20  -1.05   0.93   1.91 energies\n",
      "cost score: 7.175507677377766\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.49   5.58   0.24  11.65   0.69   2.28 weighted difference from target energies\n",
      " -8.52  11.58  10.76   0.82   1.07   1.28 energies\n",
      "cost score: 5.642874125270876\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.92   5.58  -0.71   9.74   0.89   3.55 weighted difference from target energies\n",
      " -7.24  11.58  11.71  -0.13   1.66   2.55 energies\n",
      "cost score: 5.734394742345351\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.17   4.96   1.35  12.63   0.01   1.40 weighted difference from target energies\n",
      " -9.48  10.96   9.65   1.32  -0.96   0.40 energies\n",
      "cost score: 5.042529822181041\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.36   4.44   1.36  11.61  -0.01   1.99 weighted difference from target energies\n",
      " -8.91  10.44   9.64   0.81  -1.02   0.99 energies\n",
      "cost score: 4.616138832085811\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.47   4.44   0.84  10.56   0.10   2.29 weighted difference from target energies\n",
      " -8.60  10.44  10.16   0.28  -0.71   1.29 energies\n",
      "cost score: 4.63104942494422\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.66   5.12   0.02  10.28   0.90   3.40 weighted difference from target energies\n",
      " -8.02  11.12  10.98   0.14   1.69   2.40 energies\n",
      "cost score: 5.328980388912178\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.71   5.17   0.25  10.84   0.93   2.94 weighted difference from target energies\n",
      "-10.88  11.17  10.75   0.42   1.79   1.94 energies\n",
      "cost score: 5.305821512602913\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.98   5.20   0.20  10.81   0.84   2.73 weighted difference from target energies\n",
      "-10.06  11.20  10.80   0.41   1.52   1.73 energies\n",
      "cost score: 5.314589077686378\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.12   5.31   0.22  11.05   0.29   2.44 weighted difference from target energies\n",
      " -9.64  11.31  10.78   0.53  -0.12   1.44 energies\n",
      "cost score: 5.390696307523274\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.94   4.01   2.39  12.80   1.07   4.31 weighted difference from target energies\n",
      " -7.17  10.01   8.61   1.40   2.21   3.31 energies\n",
      "cost score: 5.013468926241704\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.55   5.15   2.32  14.94   1.30   4.47 weighted difference from target energies\n",
      " -8.34  11.15   8.68   2.47   2.90   3.47 energies\n",
      "cost score: 5.628494382566681\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.98   4.85   1.10  11.89   1.11   4.43 weighted difference from target energies\n",
      " -7.05  10.85   9.90   0.95   2.33   3.43 energies\n",
      "cost score: 5.416458932823254\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.77   3.75   2.41  12.31   1.14   4.25 weighted difference from target energies\n",
      " -7.70   9.75   8.59   1.15   2.41   3.25 energies\n",
      "cost score: 4.886928443146839\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.59   3.78   2.85  13.26   0.91   3.11 weighted difference from target energies\n",
      " -8.22   9.78   8.15   1.63   1.73   2.11 energies\n",
      "cost score: 4.510947939710563\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.61   3.78   2.84  13.25   0.94   3.94 weighted difference from target energies\n",
      " -8.18   9.78   8.16   1.62   1.82   2.94 energies\n",
      "cost score: 4.78661117134773\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.27   3.73   2.83  13.12   1.37   4.69 weighted difference from target energies\n",
      " -6.18   9.73   8.17   1.56   3.11   3.69 energies\n",
      "cost score: 5.199600059111775\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.90   2.90   4.20  14.19   1.04   3.17 weighted difference from target energies\n",
      " -7.31   8.90   6.80   2.10   2.11   2.17 energies\n",
      "cost score: 4.770076588731432\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.69   5.86   2.64  16.99   0.37   3.85 weighted difference from target energies\n",
      " -7.94  11.86   8.36   3.50   0.10   2.85 energies\n",
      "cost score: 6.0361077092012865\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.81   4.72   3.25  15.94   1.23   3.99 weighted difference from target energies\n",
      " -7.57  10.72   7.75   2.97   2.68   2.99 energies\n",
      "cost score: 5.3062711407433465\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.22  -0.43   4.74   8.62  -1.05  -3.16 weighted difference from target energies\n",
      " -6.33   5.57   6.26  -0.69  -4.16  -4.16 energies\n",
      "cost score: 4.823499238427516\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.07   2.91   4.32  14.46   1.01   3.06 weighted difference from target energies\n",
      " -6.80   8.91   6.68   2.23   2.03   2.06 energies\n",
      "cost score: 4.832622354325286\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.15   3.33   4.01  14.68   0.83   2.51 weighted difference from target energies\n",
      " -6.56   9.33   6.99   2.34   1.50   1.51 energies\n",
      "cost score: 4.665134824177525\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.13   3.33   3.62  13.90   0.82   2.46 weighted difference from target energies\n",
      " -6.60   9.33   7.38   1.95   1.46   1.46 energies\n",
      "cost score: 4.473422531771035\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.11   3.34   3.57  13.82   0.79   2.38 weighted difference from target energies\n",
      " -6.68   9.34   7.43   1.91   1.38   1.38 energies\n",
      "cost score: 4.442054850693952\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.37   3.14   3.86  14.00   1.02   3.31 weighted difference from target energies\n",
      " -5.88   9.14   7.14   2.00   2.06   2.31 energies\n",
      "cost score: 4.713469724247752\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.28   2.44   4.60  14.06   1.16   4.27 weighted difference from target energies\n",
      " -6.16   8.44   6.40   2.03   2.49   3.27 energies\n",
      "cost score: 5.27311717394332\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.75   3.33   2.83  12.32   1.14   4.30 weighted difference from target energies\n",
      " -4.74   9.33   8.17   1.16   2.42   3.30 energies\n",
      "cost score: 4.922576213711335\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.17   3.63   3.33  13.91   1.14   4.27 weighted difference from target energies\n",
      " -6.49   9.63   7.67   1.96   2.43   3.27 energies\n",
      "cost score: 5.003399274905128\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.05   4.07   2.07  12.30   1.15   4.46 weighted difference from target energies\n",
      " -6.85  10.07   8.93   1.15   2.46   3.46 energies\n",
      "cost score: 5.100982999220483\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.83   4.21   2.16  12.72   0.69   4.69 weighted difference from target energies\n",
      " -7.51  10.21   8.84   1.36   1.06   3.69 energies\n",
      "cost score: 5.261751127560608\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.78   5.95   1.79  15.47   0.65   4.54 weighted difference from target energies\n",
      " -7.67  11.95   9.21   2.74   0.96   3.54 energies\n",
      "cost score: 6.198247616603378\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.77   7.05   0.57  15.24   0.65   4.03 weighted difference from target energies\n",
      " -7.68  13.05  10.43   2.62   0.94   3.03 energies\n",
      "cost score: 7.1045283679813025\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.59   5.95   1.34  14.59   1.24   5.91 weighted difference from target energies\n",
      " -5.24  11.95   9.66   2.29   2.71   4.91 energies\n",
      "cost score: 6.651138078010099\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.28   5.65   2.09  15.48   1.24   6.13 weighted difference from target energies\n",
      " -6.15  11.65   8.91   2.74   2.71   5.13 energies\n",
      "cost score: 6.638871022650288\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.41   5.34   2.62  15.93   1.20   6.24 weighted difference from target energies\n",
      " -5.76  11.34   8.38   2.96   2.60   5.24 energies\n",
      "cost score: 6.620312953720225\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.53   5.38   2.24  15.24   0.95   6.16 weighted difference from target energies\n",
      " -5.41  11.38   8.76   2.62   1.86   5.16 energies\n",
      "cost score: 6.5734900677450705\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.43   5.20   2.15  14.70   1.28   5.47 weighted difference from target energies\n",
      " -5.72  11.20   8.85   2.35   2.84   4.47 energies\n",
      "cost score: 6.09260529123952\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.45   5.20   2.09  14.58   1.23   5.50 weighted difference from target energies\n",
      " -5.65  11.20   8.91   2.29   2.69   4.50 energies\n",
      "cost score: 6.107464495977393\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.75   6.48  -0.32  12.32   0.96   6.33 weighted difference from target energies\n",
      " -4.76  12.48  11.32   1.16   1.88   5.33 energies\n",
      "cost score: 7.118923659791201\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.79   4.21   0.49   9.39   0.96   6.33 weighted difference from target energies\n",
      " -4.64  10.21  10.51  -0.31   1.88   5.33 energies\n",
      "cost score: 6.475217562841096\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.57   7.62  -1.04  13.17   0.97   6.17 weighted difference from target energies\n",
      " -5.30  13.62  12.04   1.59   1.90   5.17 energies\n",
      "cost score: 7.839322355458317\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.45   4.18   1.51  11.39   1.16   5.76 weighted difference from target energies\n",
      " -5.65  10.18   9.49   0.70   2.49   4.76 energies\n",
      "cost score: 5.996937780210657\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.39   3.30   0.93   8.46   1.18   5.76 weighted difference from target energies\n",
      " -5.82   9.30  10.07  -0.77   2.53   4.76 energies\n",
      "cost score: 5.889454209408404\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  3.00   2.46   0.69   6.31   1.16   5.57 weighted difference from target energies\n",
      " -3.99   8.46  10.31  -1.84   2.48   4.57 energies\n",
      "cost score: 5.702229504930516\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  3.03   2.49   1.93   8.82   1.08   5.37 weighted difference from target energies\n",
      " -3.91   8.49   9.07  -0.59   2.23   4.37 energies\n",
      "cost score: 5.550514237861985\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  3.00   2.46   1.72   8.36   1.03   5.24 weighted difference from target energies\n",
      " -4.00   8.46   9.28  -0.82   2.09   4.24 energies\n",
      "cost score: 5.432904161532225\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  3.00   2.47   1.97   8.89   0.81   4.80 weighted difference from target energies\n",
      " -4.00   8.47   9.03  -0.55   1.42   3.80 energies\n",
      "cost score: 5.092998232400684\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.73   1.91   3.36  10.52   0.80   4.96 weighted difference from target energies\n",
      " -4.80   7.91   7.64   0.26   1.41   3.96 energies\n",
      "cost score: 5.276170355827672\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.57   3.85   2.62  12.93   0.82   4.68 weighted difference from target energies\n",
      " -5.30   9.85   8.38   1.47   1.47   3.68 energies\n",
      "cost score: 5.212852475820793\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.68   3.92   2.47  12.78   0.84   4.63 weighted difference from target energies\n",
      " -4.96   9.92   8.53   1.39   1.53   3.63 energies\n",
      "cost score: 5.20182684355172\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.74   3.79   2.07  11.72   0.82   4.78 weighted difference from target energies\n",
      " -4.79   9.79   8.93   0.86   1.47   3.78 energies\n",
      "cost score: 5.242037450873505\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.75   3.72   2.11  11.67   0.82   4.77 weighted difference from target energies\n",
      " -4.75   9.72   8.89   0.83   1.46   3.77 energies\n",
      "cost score: 5.223051309621485\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.76   3.74   1.97  11.43   0.92   4.52 weighted difference from target energies\n",
      " -4.72   9.74   9.03   0.72   1.75   3.52 energies\n",
      "cost score: 5.072613693912755\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.75   3.69   2.53  12.44   0.96   4.48 weighted difference from target energies\n",
      " -4.75   9.69   8.47   1.22   1.89   3.48 energies\n",
      "cost score: 5.06946546570854\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.79   3.65   2.35  12.01   0.89   4.65 weighted difference from target energies\n",
      " -4.63   9.65   8.65   1.00   1.68   3.65 energies\n",
      "cost score: 5.14984500588617\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.79   3.65   2.35  12.01   0.89   4.65 weighted difference from target energies\n",
      " -4.63   9.65   8.65   1.01   1.68   3.65 energies\n",
      "cost score: 5.150130307238585\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.61   3.56   2.96  13.04   1.10   4.71 weighted difference from target energies\n",
      " -5.18   9.56   8.04   1.52   2.30   3.71 energies\n",
      "cost score: 5.204281558614362\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.17   4.97  -0.06   9.81   0.21   0.62 weighted difference from target energies\n",
      " -9.49  10.97  11.06  -0.09  -0.38  -0.38 energies\n",
      "cost score: 5.014859434302829\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.78   4.97   0.28  10.50   0.81   2.43 weighted difference from target energies\n",
      " -7.66  10.97  10.72   0.25   1.43   1.43 energies\n",
      "cost score: 5.101729983833183\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.24   4.86   0.09   9.91   0.58   1.74 weighted difference from target energies\n",
      " -9.29  10.86  10.91  -0.04   0.74   0.74 energies\n",
      "cost score: 4.9508030471456985\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.03   5.71   0.01  11.43   0.84   2.72 weighted difference from target energies\n",
      " -6.91  11.71  10.99   0.72   1.53   1.72 energies\n",
      "cost score: 5.790550959611218\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.24   5.16  -0.04  10.23   0.58   1.73 weighted difference from target energies\n",
      " -9.29  11.16  11.04   0.12   0.73   0.73 energies\n",
      "cost score: 5.224826354831393\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.24   5.19  -0.08  10.21   0.58   1.75 weighted difference from target energies\n",
      " -9.27  11.19  11.08   0.10   0.75   0.75 energies\n",
      "cost score: 5.250331723762682\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.42   4.84   0.34  10.36   0.71   2.13 weighted difference from target energies\n",
      " -8.75  10.84  10.66   0.18   1.13   1.13 energies\n",
      "cost score: 4.960776178422635\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.57   4.90   0.58  10.98   0.54   1.62 weighted difference from target energies\n",
      " -8.30  10.90  10.42   0.49   0.62   0.62 energies\n",
      "cost score: 4.998325110255452\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.64   6.67  -0.13  13.08   0.65   1.94 weighted difference from target energies\n",
      " -8.08  12.67  11.13   1.54   0.94   0.94 energies\n",
      "cost score: 6.688935600458033\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.98   5.75  -0.56  10.38   0.80   2.39 weighted difference from target energies\n",
      " -7.06  11.75  11.56   0.19   1.39   1.39 energies\n",
      "cost score: 5.810344269345532\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.94   6.10  -0.36  11.48   0.95   2.86 weighted difference from target energies\n",
      " -7.17  12.10  11.36   0.74   1.86   1.86 energies\n",
      "cost score: 6.160364084112723\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.85   6.56   0.67  14.47   1.11   3.33 weighted difference from target energies\n",
      " -7.45  12.56  10.33   2.24   2.33   2.33 energies\n",
      "cost score: 6.615149933472144\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.95   6.16  -0.41  11.51   0.96   2.89 weighted difference from target energies\n",
      " -7.16  12.16  11.41   0.75   1.89   1.89 energies\n",
      "cost score: 6.2163358665653226\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.99   6.20  -0.19  12.03   1.07   3.22 weighted difference from target energies\n",
      " -7.02  12.20  11.19   1.01   2.22   2.22 energies\n",
      "cost score: 6.273489169983282\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.69   5.21  -0.21  10.00   1.26   4.06 weighted difference from target energies\n",
      " -4.92  11.21  11.21   0.00   2.79   3.06 energies\n",
      "cost score: 5.564498374127178\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.64   5.21  -0.21  10.00   1.21   4.63 weighted difference from target energies\n",
      " -5.08  11.21  11.21  -0.00   2.64   3.63 energies\n",
      "cost score: 5.718767018205636\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.00   5.21  -0.20  10.02   0.70   2.32 weighted difference from target energies\n",
      " -7.00  11.21  11.20   0.01   1.10   1.32 energies\n",
      "cost score: 5.319033253031941\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.17   4.95   0.42  10.73   0.52   1.76 weighted difference from target energies\n",
      " -9.48  10.95  10.58   0.36   0.55   0.76 energies\n",
      "cost score: 5.030525434514627\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.87   4.83   0.46  10.58  -0.22   1.34 weighted difference from target energies\n",
      "-10.38  10.83  10.54   0.29  -1.66   0.34 energies\n",
      "cost score: 4.898137089586851\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.88   4.83   0.46  10.58  -0.22   1.35 weighted difference from target energies\n",
      "-10.37  10.83  10.54   0.29  -1.65   0.35 energies\n",
      "cost score: 4.898557429564476\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.88   4.83   0.44  10.55  -0.21   1.38 weighted difference from target energies\n",
      "-10.35  10.83  10.56   0.27  -1.63   0.38 energies\n",
      "cost score: 4.899887810022294\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.49   4.94   0.50  10.88   0.15   2.16 weighted difference from target energies\n",
      " -8.54  10.94  10.50   0.44  -0.55   1.16 energies\n",
      "cost score: 5.047134263241323\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.40   2.98   2.72  11.39   0.16   2.19 weighted difference from target energies\n",
      " -8.79   8.98   8.28   0.69  -0.51   1.19 energies\n",
      "cost score: 3.890247512726054\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.58   1.12   4.13  10.51   0.63   2.33 weighted difference from target energies\n",
      " -8.26   7.12   6.87   0.25   0.88   1.33 energies\n",
      "cost score: 4.408621275297529\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.04   3.13   2.74  11.75   0.65   2.74 weighted difference from target energies\n",
      " -6.87   9.13   8.26   0.87   0.94   1.74 energies\n",
      "cost score: 4.15114561431637\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.92   3.17   2.75  11.85   0.47   2.22 weighted difference from target energies\n",
      " -7.25   9.17   8.25   0.92   0.40   1.22 energies\n",
      "cost score: 4.045417213386783\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.46   3.01   2.76  11.55   0.86   3.43 weighted difference from target energies\n",
      " -5.61   9.01   8.24   0.77   1.58   2.43 energies\n",
      "cost score: 4.396050701250072\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.59   3.61   2.73  12.68   0.81   2.42 weighted difference from target energies\n",
      " -8.23   9.61   8.27   1.34   1.42   1.42 energies\n",
      "cost score: 4.25853235576877\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.74   3.83   2.02  11.71   0.93   2.78 weighted difference from target energies\n",
      " -7.77   9.83   8.98   0.85   1.78   1.78 energies\n",
      "cost score: 4.356985934436511\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.66   3.06   1.98  10.09   1.01   3.04 weighted difference from target energies\n",
      " -8.02   9.06   9.02   0.04   2.04   2.04 energies\n",
      "cost score: 4.052818362504506\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.57   4.42   0.88  10.60   0.85   2.54 weighted difference from target energies\n",
      " -8.28  10.42  10.12   0.30   1.54   1.54 energies\n",
      "cost score: 4.657366360729375\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.09   4.42   0.90  10.65   1.28   3.85 weighted difference from target energies\n",
      " -6.73  10.42  10.10   0.32   2.85   2.85 energies\n",
      "cost score: 4.9716991723544615\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.57   4.42   0.88  10.60   0.85   2.55 weighted difference from target energies\n",
      " -8.28  10.42  10.12   0.30   1.55   1.55 energies\n",
      "cost score: 4.6586613261269285\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.10   5.10   0.46  11.11   0.34   1.03 weighted difference from target energies\n",
      " -9.71  11.10  10.54   0.56   0.03   0.03 energies\n",
      "cost score: 5.151075254374317\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.06   6.14  -0.64  11.01   0.33   1.00 weighted difference from target energies\n",
      " -9.82  12.14  11.64   0.50   0.00   0.00 energies\n",
      "cost score: 6.155189761898691\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.12   4.87   0.65  11.05   0.36   1.09 weighted difference from target energies\n",
      " -9.65  10.87  10.35   0.52   0.09   0.09 energies\n",
      "cost score: 4.939720532408669\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.52   4.87   0.66  11.06   0.96   4.37 weighted difference from target energies\n",
      " -5.43  10.87  10.34   0.53   1.88   3.37 energies\n",
      "cost score: 5.4223179773180155\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.44   5.78   0.41  12.38   1.06   4.89 weighted difference from target energies\n",
      " -5.68  11.78  10.59   1.19   2.19   3.89 energies\n",
      "cost score: 6.156453348358024\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.30   6.03   0.74  13.53   1.39   4.89 weighted difference from target energies\n",
      " -6.10  12.03  10.26   1.77   3.18   3.89 energies\n",
      "cost score: 6.332859586759513\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.52   4.99   0.53  11.04   0.96   4.37 weighted difference from target energies\n",
      " -5.43  10.99  10.47   0.52   1.88   3.37 energies\n",
      "cost score: 5.489862373033815\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.59   5.24   1.17  12.81   0.88   4.77 weighted difference from target energies\n",
      " -5.22  11.24   9.83   1.41   1.64   3.77 energies\n",
      "cost score: 5.785747248587876\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.58   6.02  -0.82  10.40   0.87   4.74 weighted difference from target energies\n",
      " -5.25  12.02  11.82   0.20   1.61   3.74 energies\n",
      "cost score: 6.292478142166789\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.73   5.20   0.95  12.30   0.77   4.72 weighted difference from target energies\n",
      " -4.80  11.20  10.05   1.15   1.30   3.72 energies\n",
      "cost score: 5.749487604744487\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.89   7.00   0.82  15.63  -1.11  -3.32 weighted difference from target energies\n",
      " -4.32  13.00  10.18   2.81  -4.32  -4.32 energies\n",
      "cost score: 7.015413864694353\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.34   5.73   0.76  12.97   0.78   3.41 weighted difference from target energies\n",
      " -5.98  11.73  10.24   1.48   1.35   2.41 energies\n",
      "cost score: 5.8652928193340115\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.42   3.62   1.44  10.11   0.96   3.90 weighted difference from target energies\n",
      " -5.73   9.62   9.56   0.05   1.89   2.90 energies\n",
      "cost score: 4.65174599704138\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.58   2.12   1.31   6.85   1.19   4.51 weighted difference from target energies\n",
      " -5.26   8.12   9.69  -1.57   2.56   3.51 energies\n",
      "cost score: 4.782596978731074\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.82  -0.36   5.35   9.99   0.45   1.79 weighted difference from target energies\n",
      " -7.54   5.64   5.65  -0.01   0.34   0.79 energies\n",
      "cost score: 5.41733701297235\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.74  -0.36   5.36  10.00   0.43   1.72 weighted difference from target energies\n",
      " -7.79   5.64   5.64  -0.00   0.30   0.72 energies\n",
      "cost score: 5.422283619462318\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.78  -0.36   5.36  10.00   0.48   1.87 weighted difference from target energies\n",
      " -7.66   5.64   5.64   0.00   0.44   0.87 energies\n",
      "cost score: 5.427754372750208\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.76  -0.36   5.36  10.00   0.45   1.79 weighted difference from target energies\n",
      " -7.73   5.64   5.64  -0.00   0.36   0.79 energies\n",
      "cost score: 5.423207635977062\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.39  -0.17   5.16   9.97   0.76   3.75 weighted difference from target energies\n",
      " -5.83   5.83   5.84  -0.01   1.28   2.75 energies\n",
      "cost score: 5.439720041182657\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.39  -0.27   5.25   9.97   0.74   3.75 weighted difference from target energies\n",
      " -5.83   5.73   5.75  -0.01   1.23   2.75 energies\n",
      "cost score: 5.509574270519715\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.33  -0.26   5.21   9.91   0.75   3.69 weighted difference from target energies\n",
      " -6.01   5.74   5.79  -0.05   1.24   2.69 energies\n",
      "cost score: 5.466352523813835\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.48  -0.29   5.24   9.90  -0.01   2.14 weighted difference from target energies\n",
      " -5.55   5.71   5.76  -0.05  -1.03   1.14 energies\n",
      "cost score: 5.350120704857543\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.77   1.42   2.91   8.67   0.28   1.02 weighted difference from target energies\n",
      "-10.69   7.42   8.09  -0.67  -0.15   0.02 energies\n",
      "cost score: 3.3584431313563634\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.79   1.44   1.36   5.60   0.41   2.60 weighted difference from target energies\n",
      " -7.64   7.44   9.64  -2.20   0.23   1.60 energies\n",
      "cost score: 3.368943698402215\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.56   5.14  -0.16   9.95   0.16   0.47 weighted difference from target energies\n",
      "-11.31  11.14  11.16  -0.02  -0.53  -0.53 energies\n",
      "cost score: 5.169543831695812\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.50   1.43   1.74   6.33   0.82   6.13 weighted difference from target energies\n",
      " -5.50   7.43   9.26  -1.83   1.47   5.13 energies\n",
      "cost score: 6.181580187768052\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.83   3.43   1.26   9.37   1.64   5.62 weighted difference from target energies\n",
      " -4.51   9.43   9.74  -0.31   3.91   4.62 energies\n",
      "cost score: 5.806090533298879\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.06  -0.46   2.43   3.94  -0.94   3.14 weighted difference from target energies\n",
      " -6.82   5.54   8.57  -3.03  -3.81   2.14 energies\n",
      "cost score: 3.768380337565045\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  3.01   6.55  -0.31  12.48  -0.99  -2.98 weighted difference from target energies\n",
      " -3.98  12.55  11.31   1.24  -3.98  -3.98 energies\n",
      "cost score: 6.580693915766253\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.90  -0.56   2.75   4.39   0.48   3.16 weighted difference from target energies\n",
      " -7.30   5.44   8.25  -2.80   0.44   2.16 energies\n",
      "cost score: 3.874383417505491\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.98  -0.50   2.77   4.53  -0.94   3.07 weighted difference from target energies\n",
      " -7.07   5.50   8.23  -2.73  -3.81   2.07 energies\n",
      "cost score: 3.822739387611078\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.19  -0.50   2.04   3.08  -0.94   3.02 weighted difference from target energies\n",
      " -9.44   5.50   8.96  -3.46  -3.81   2.02 energies\n",
      "cost score: 3.4807034395558256\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.14  -0.54   2.30   3.53  -0.93   2.86 weighted difference from target energies\n",
      " -9.58   5.46   8.70  -3.23  -3.78   1.86 energies\n",
      "cost score: 3.4527480360946736\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.14  -0.54   2.26   3.44  -0.93   2.86 weighted difference from target energies\n",
      " -9.59   5.46   8.74  -3.28  -3.78   1.86 energies\n",
      "cost score: 3.4386198561596912\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.12  -0.54   2.31   3.54  -0.91   2.80 weighted difference from target energies\n",
      " -9.65   5.46   8.69  -3.23  -3.74   1.80 energies\n",
      "cost score: 3.418170015627915\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.18   0.25   1.79   4.08   1.43   4.42 weighted difference from target energies\n",
      " -9.47   6.25   9.21  -2.96   3.30   3.42 energies\n",
      "cost score: 4.582901470438039\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.02  -0.12   2.85   5.45   1.01   3.41 weighted difference from target energies\n",
      " -6.95   5.88   8.15  -2.28   2.02   2.41 energies\n",
      "cost score: 4.071525985710283\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.10   0.60   2.23   5.67   1.06   3.49 weighted difference from target energies\n",
      " -6.71   6.60   8.77  -2.16   2.18   2.49 energies\n",
      "cost score: 4.006631980543684\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.49   0.92   0.78   3.41   0.95   5.11 weighted difference from target energies\n",
      " -5.53   6.92  10.22  -3.30   1.85   4.11 energies\n",
      "cost score: 5.220449616371115\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.06   0.62   3.08   7.39   1.00   3.36 weighted difference from target energies\n",
      " -6.82   6.62   7.92  -1.30   2.00   2.36 energies\n",
      "cost score: 4.141158638415286\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.53   3.50   0.15   7.31   0.93   3.48 weighted difference from target energies\n",
      " -8.40   9.50  10.85  -1.34   1.80   2.48 energies\n",
      "cost score: 4.304476175362412\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.67   3.50  -0.19   6.62   1.07   3.88 weighted difference from target energies\n",
      " -7.99   9.50  11.19  -1.69   2.20   2.88 energies\n",
      "cost score: 4.5076535131795294\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.25   5.69   0.13  11.65   0.30   3.07 weighted difference from target energies\n",
      " -9.25  11.69  10.87   0.82  -0.10   2.07 energies\n",
      "cost score: 5.781190320835324\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.65   3.65  -0.65   6.00   1.03   3.82 weighted difference from target energies\n",
      " -8.06   9.65  11.65  -2.00   2.09   2.82 energies\n",
      "cost score: 4.529997409899742\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.19   3.66  -1.23   4.84   1.41   5.37 weighted difference from target energies\n",
      " -6.44   9.66  12.23  -2.58   3.23   4.37 energies\n",
      "cost score: 5.586584763239979\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.70   2.31   0.13   4.89   1.05   3.76 weighted difference from target energies\n",
      " -7.89   8.31  10.87  -2.56   2.14   2.76 energies\n",
      "cost score: 4.135365620995269\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.64   2.24  -2.60  -0.73   1.15   6.55 weighted difference from target energies\n",
      " -5.08   8.24  13.60  -5.36   2.44   5.55 energies\n",
      "cost score: 6.587350526605486\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.55   2.31   0.44   5.51   0.89   3.30 weighted difference from target energies\n",
      " -8.36   8.31  10.56  -2.25   1.67   2.30 energies\n",
      "cost score: 3.8259637507903603\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.73   3.73  -0.02   7.43   0.92   3.89 weighted difference from target energies\n",
      " -7.80   9.73  11.02  -1.29   1.76   2.89 energies\n",
      "cost score: 4.602384873832024\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.54   0.52   2.30   5.65   0.45   2.88 weighted difference from target energies\n",
      " -5.37   6.52   8.70  -2.18   0.36   1.88 energies\n",
      "cost score: 3.779788270686071\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.54  -0.06   2.84   5.55   0.47   2.92 weighted difference from target energies\n",
      " -5.38   5.94   8.16  -2.22   0.40   1.92 energies\n",
      "cost score: 3.9288791086064614\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.54  -0.06   2.92   5.71   0.47   2.93 weighted difference from target energies\n",
      " -5.38   5.94   8.08  -2.15   0.40   1.93 energies\n",
      "cost score: 3.959432388751039\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.54  -0.07   2.84   5.54   0.46   2.91 weighted difference from target energies\n",
      " -5.39   5.93   8.16  -2.23   0.39   1.91 energies\n",
      "cost score: 3.9231044761391374\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.55  -1.15   3.89   5.49   0.55   3.23 weighted difference from target energies\n",
      " -5.36   4.85   7.11  -2.26   0.66   2.23 energies\n",
      "cost score: 4.48960218600862\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.56  -0.14   3.30   6.31   0.49   2.93 weighted difference from target energies\n",
      " -5.31   5.86   7.70  -1.84   0.46   1.93 energies\n",
      "cost score: 4.116206519825829\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.81  -0.14   4.46   8.63  -0.05   1.18 weighted difference from target energies\n",
      " -7.57   5.86   6.54  -0.68  -1.14   0.18 energies\n",
      "cost score: 4.5819557524484535\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.88   3.61   1.64  10.51  -0.75   4.66 weighted difference from target energies\n",
      " -7.36   9.61   9.36   0.25  -3.24   3.66 energies\n",
      "cost score: 5.042701147240236\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.93   5.03  -0.71   8.63   1.26   5.99 weighted difference from target energies\n",
      " -4.21  11.03  11.71  -0.69   2.78   4.99 energies\n",
      "cost score: 6.353456145300291\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.94   5.07  -0.83   8.48   1.25   6.26 weighted difference from target energies\n",
      " -4.19  11.07  11.83  -0.76   2.74   5.26 energies\n",
      "cost score: 6.55768427501941\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.93   6.85  -1.59  10.52   1.22   5.71 weighted difference from target energies\n",
      "-10.22  12.85  12.59   0.26   2.67   4.71 energies\n",
      "cost score: 7.134995971879218\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.92   6.61  -2.11   8.99   1.23   5.99 weighted difference from target energies\n",
      " -4.25  12.61  13.11  -0.50   2.69   4.99 energies\n",
      "cost score: 7.057275121387452\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.92   4.64  -0.14   8.99   1.23   5.97 weighted difference from target energies\n",
      " -4.25  10.64  11.14  -0.50   2.68   4.97 energies\n",
      "cost score: 6.249750815616738\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.88   4.91  -0.92   7.97   1.18   5.93 weighted difference from target energies\n",
      " -4.35  10.91  11.92  -1.02   2.55   4.93 energies\n",
      "cost score: 6.278149478260183\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.88   4.95  -0.86   8.17   1.14   4.57 weighted difference from target energies\n",
      " -7.36  10.95  11.86  -0.92   2.43   3.57 energies\n",
      "cost score: 5.511362587537325\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.91   7.88  -4.01   7.76   1.15   4.59 weighted difference from target energies\n",
      " -7.27  13.88  15.01  -1.12   2.44   3.59 energies\n",
      "cost score: 7.923874833948696\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.91   7.88  -3.32   9.12   1.15   4.61 weighted difference from target energies\n",
      " -7.26  13.88  14.32  -0.44   2.46   3.61 energies\n",
      "cost score: 7.925576600472613\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.31   7.42  -1.03  12.79   0.71   4.21 weighted difference from target energies\n",
      " -9.08  13.42  12.03   1.39   1.12   3.21 energies\n",
      "cost score: 7.466776050181686\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.92   9.09  -0.79  16.60   1.65   5.86 weighted difference from target energies\n",
      " -7.25  15.09  11.79   3.30   3.96   4.86 energies\n",
      "cost score: 9.133035685564783\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.03   8.99  -0.71  16.56   1.87   6.71 weighted difference from target energies\n",
      " -6.92  14.99  11.71   3.28   4.61   5.71 energies\n",
      "cost score: 9.092556727989221\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.42   9.46  -0.71  17.50   2.31   7.37 weighted difference from target energies\n",
      " -5.75  15.46  11.71   3.75   5.94   6.37 energies\n",
      "cost score: 9.579684789625581\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.04  11.53  -2.31  18.44   2.02   6.83 weighted difference from target energies\n",
      " -6.87  17.53  13.31   4.22   5.05   5.83 energies\n",
      "cost score: 11.536787049472487\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.21   8.83  -1.16  15.34   1.12   4.27 weighted difference from target energies\n",
      " -9.36  14.83  12.16   2.67   2.36   3.27 energies\n",
      "cost score: 8.84599773664844\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.13   9.43  -2.15  14.55   1.19   4.09 weighted difference from target energies\n",
      " -9.61  15.43  13.15   2.28   2.58   3.09 energies\n",
      "cost score: 9.430823442750539\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.51   9.13  -2.64  12.97   1.16   4.58 weighted difference from target energies\n",
      " -8.48  15.13  13.64   1.49   2.47   3.58 energies\n",
      "cost score: 9.141808736253711\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.08   5.37   0.63  11.99   1.45   5.69 weighted difference from target energies\n",
      " -6.77  11.37  10.37   1.00   3.35   4.69 energies\n",
      "cost score: 6.261547104843505\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.15   7.33   0.67  16.01   0.46   1.37 weighted difference from target energies\n",
      " -6.56  13.33  10.33   3.00   0.37   0.37 energies\n",
      "cost score: 7.3420680624542785\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.50   5.38   2.35  15.46   1.19   4.60 weighted difference from target energies\n",
      " -8.50  11.38   8.65   2.73   2.57   3.60 energies\n",
      "cost score: 5.810467695740174\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.32   7.18  -0.13  14.12   1.01   4.26 weighted difference from target energies\n",
      " -9.04  13.18  11.13   2.06   2.04   3.26 energies\n",
      "cost score: 7.2424220903059195\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.33   6.68   0.30  13.97   1.01   4.27 weighted difference from target energies\n",
      " -9.02  12.68  10.70   1.99   2.04   3.27 energies\n",
      "cost score: 6.777584075677799\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.25   6.56   0.22  13.56   0.92   4.02 weighted difference from target energies\n",
      " -9.24  12.56  10.78   1.78   1.76   3.02 energies\n",
      "cost score: 6.642541820885011\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.25   6.56  -0.30  12.53   0.92   4.00 weighted difference from target energies\n",
      " -9.26  12.56  11.30   1.27   1.75   3.00 energies\n",
      "cost score: 6.647580908760373\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.31   8.36  -1.40  13.92   1.09   4.09 weighted difference from target energies\n",
      " -9.06  14.36  12.40   1.96   2.26   3.09 energies\n",
      "cost score: 8.378774080111048\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.24   7.06  -0.67  12.77   0.92   3.99 weighted difference from target energies\n",
      " -9.27  13.06  11.67   1.39   1.76   2.99 energies\n",
      "cost score: 7.109689114811108\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.74   7.06   0.72  15.56   1.36   5.49 weighted difference from target energies\n",
      " -7.78  13.06  10.28   2.78   3.09   4.49 energies\n",
      "cost score: 7.258394713936494\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.33   6.40   0.09  12.97   1.39   5.66 weighted difference from target energies\n",
      " -6.02  12.40  10.91   1.48   3.16   4.66 energies\n",
      "cost score: 6.806487926823836\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.31   8.39  -2.07  12.64   1.48   5.65 weighted difference from target energies\n",
      " -6.08  14.39  13.07   1.32   3.43   4.65 energies\n",
      "cost score: 8.455615627927843\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.29   8.30  -2.07  12.46   1.54   5.58 weighted difference from target energies\n",
      " -6.13  14.30  13.07   1.23   3.63   4.58 energies\n",
      "cost score: 8.371007749151566\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  3.02   9.30  -5.41   7.77   1.72   6.42 weighted difference from target energies\n",
      " -3.94  15.30  16.41  -1.12   4.17   5.42 energies\n",
      "cost score: 9.35378359928564\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.29   6.10  -0.83  10.54   1.52   5.54 weighted difference from target energies\n",
      " -6.13  12.10  11.83   0.27   3.57   4.54 energies\n",
      "cost score: 6.571297568370262\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.18   3.13   2.01  10.29   0.73   2.95 weighted difference from target energies\n",
      " -6.45   9.13   8.99   0.14   1.18   1.95 energies\n",
      "cost score: 4.1016443764360755\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.20   2.86   2.19  10.11   0.65   3.29 weighted difference from target energies\n",
      " -6.41   8.86   8.81   0.06   0.95   2.29 energies\n",
      "cost score: 4.162554517939222\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.37   6.55   1.47  16.04  -0.11  -0.33 weighted difference from target energies\n",
      " -5.89  12.55   9.53   3.02  -1.33  -1.33 energies\n",
      "cost score: 6.571961513716246\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.09   5.20   1.97  14.34   1.04   4.53 weighted difference from target energies\n",
      " -6.73  11.20   9.03   2.17   2.11   3.53 energies\n",
      "cost score: 5.6746999743980195\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.50   3.37   3.90  14.54   1.14   4.00 weighted difference from target energies\n",
      " -8.51   9.37   7.10   2.27   2.42   3.00 energies\n",
      "cost score: 4.946860652639792\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.94   4.69   2.54  14.45   0.57   2.92 weighted difference from target energies\n",
      "-10.19  10.69   8.46   2.23   0.70   1.92 energies\n",
      "cost score: 4.971746692322211\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.87   4.69   4.03  17.44   0.90   2.70 weighted difference from target energies\n",
      "-10.40  10.69   6.97   3.72   1.69   1.70 energies\n",
      "cost score: 5.219431025487229\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.93   4.64   2.58  14.44   0.56   2.91 weighted difference from target energies\n",
      "-10.20  10.64   8.42   2.22   0.69   1.91 energies\n",
      "cost score: 4.937233180802073\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.98   4.94   2.77  15.43   0.61   3.06 weighted difference from target energies\n",
      "-10.05  10.94   8.23   2.72   0.83   2.06 energies\n",
      "cost score: 5.2048992751851015\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.30   3.25   5.18  16.85   0.70   3.80 weighted difference from target energies\n",
      " -9.10   9.25   5.82   3.42   1.10   2.80 energies\n",
      "cost score: 5.533785557960146\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.07   5.68   3.92  19.21   0.66   3.32 weighted difference from target energies\n",
      " -9.78  11.68   7.08   4.61   0.98   2.32 energies\n",
      "cost score: 5.930871579782875\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.13   4.91   2.79  15.41   0.92   3.80 weighted difference from target energies\n",
      " -9.61  10.91   8.21   2.70   1.77   2.80 energies\n",
      "cost score: 5.31043671413051\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.88   5.62   1.26  13.75   0.72   3.07 weighted difference from target energies\n",
      "-10.35  11.62   9.74   1.87   1.15   2.07 energies\n",
      "cost score: 5.718355303768424\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.45   4.65   3.61  16.52   0.21   2.03 weighted difference from target energies\n",
      "-11.66  10.65   7.39   3.26  -0.37   1.03 energies\n",
      "cost score: 5.024604669721035\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.54   3.96   3.97  15.86   0.16   2.33 weighted difference from target energies\n",
      "-11.37   9.96   7.03   2.93  -0.52   1.33 energies\n",
      "cost score: 4.7765173221385835\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.07   4.12   3.64  15.53   0.69   3.69 weighted difference from target energies\n",
      " -9.80  10.12   7.36   2.77   1.08   2.69 energies\n",
      "cost score: 4.976122612732273\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.13   4.07   3.65  15.43   0.72   3.83 weighted difference from target energies\n",
      " -9.62  10.07   7.35   2.72   1.17   2.83 energies\n",
      "cost score: 4.997876105754859\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.65   1.69   3.85  11.08   1.02   4.35 weighted difference from target energies\n",
      " -8.04   7.69   7.15   0.54   2.06   3.35 energies\n",
      "cost score: 4.926975197465274\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.81   1.27   4.05  10.65   1.30   4.89 weighted difference from target energies\n",
      " -7.57   7.27   6.95   0.32   2.91   3.89 energies\n",
      "cost score: 5.316857918498841\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.12   1.01   0.18   2.37   1.90   6.28 weighted difference from target energies\n",
      " -6.63   7.01  10.82  -3.81   4.70   5.28 energies\n",
      "cost score: 6.314942568923407\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.54   1.80   0.94   5.49   1.52   6.48 weighted difference from target energies\n",
      " -5.37   7.80  10.06  -2.25   3.55   5.48 energies\n",
      "cost score: 6.51898245887043\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.52   5.87  -0.34  11.06   1.33   6.36 weighted difference from target energies\n",
      " -5.43  11.87  11.34   0.53   2.99   5.36 energies\n",
      "cost score: 6.856539102702382\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.62   4.85  -1.06   7.59   1.68   6.51 weighted difference from target energies\n",
      " -5.14  10.85  12.06  -1.21   4.04   5.51 energies\n",
      "cost score: 6.7078586829162\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.83   4.85  -1.20   7.30   1.90   7.16 weighted difference from target energies\n",
      " -4.50  10.85  12.20  -1.35   4.69   6.16 energies\n",
      "cost score: 7.271298948991935\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.65   3.97   0.46   8.85   1.77   6.84 weighted difference from target energies\n",
      " -5.06   9.97  10.54  -0.58   4.31   5.84 energies\n",
      "cost score: 6.916615279859657\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.83   3.97   0.43   8.80   2.12   7.38 weighted difference from target energies\n",
      " -4.52   9.97  10.57  -0.60   5.37   6.38 energies\n",
      "cost score: 7.428473224610651\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.27   4.53   0.40   9.85   1.82   6.48 weighted difference from target energies\n",
      " -6.19  10.53  10.60  -0.07   4.46   5.48 energies\n",
      "cost score: 6.636216790268286\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.66   3.34   1.09   8.85   1.39   4.58 weighted difference from target energies\n",
      " -8.03   9.34   9.91  -0.57   3.17   3.58 energies\n",
      "cost score: 4.9271068802581395\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.42   2.95   1.01   7.92   1.04   4.08 weighted difference from target energies\n",
      " -8.75   8.95   9.99  -1.04   2.12   3.08 energies\n",
      "cost score: 4.476084620793507\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.42   2.73   2.92  11.30   1.12   4.52 weighted difference from target energies\n",
      " -8.74   8.73   8.08   0.65   2.36   3.52 energies\n",
      "cost score: 4.88987397981982\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.68   6.82   2.93  19.50   0.44   2.19 weighted difference from target energies\n",
      "-10.95  12.82   8.07   4.75   0.31   1.19 energies\n",
      "cost score: 6.858000669685504\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.50   2.56   2.95  11.02   1.13   4.57 weighted difference from target energies\n",
      " -8.51   8.56   8.05   0.51   2.40   3.57 energies\n",
      "cost score: 4.913984914326354\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.42   1.55   1.16   5.42   1.10   4.09 weighted difference from target energies\n",
      " -8.74   7.55   9.84  -2.29   2.31   3.09 energies\n",
      "cost score: 4.31489117406696\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.42   1.56   1.16   5.43   1.10   4.07 weighted difference from target energies\n",
      " -8.74   7.56   9.84  -2.29   2.29   3.07 energies\n",
      "cost score: 4.2988141841180765\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.39   1.65   1.22   5.72   1.06   3.57 weighted difference from target energies\n",
      " -8.83   7.65   9.78  -2.14   2.19   2.57 energies\n",
      "cost score: 3.93161463611902\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.27   1.91   2.10   8.02   0.26   2.48 weighted difference from target energies\n",
      " -9.20   7.91   8.90  -0.99  -0.22   1.48 energies\n",
      "cost score: 3.4563873628682953\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.39   1.76   1.82   7.16   0.72   2.77 weighted difference from target energies\n",
      " -8.84   7.76   9.18  -1.42   1.16   1.77 energies\n",
      "cost score: 3.5260655710243975\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.12   3.61   2.53  12.28   0.52   2.40 weighted difference from target energies\n",
      " -9.63   9.61   8.47   1.14   0.55   1.40 energies\n",
      "cost score: 4.178924849226193\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.47   1.34   1.35   5.38   1.20   4.11 weighted difference from target energies\n",
      " -8.58   7.34   9.65  -2.31   2.59   3.11 energies\n",
      "cost score: 4.334691078931391\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.04   3.75   1.55  10.61   0.06   1.78 weighted difference from target energies\n",
      " -9.88   9.75   9.45   0.30  -0.82   0.78 energies\n",
      "cost score: 4.0467559439563825\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.10   3.75   0.32   8.14   0.17   0.51 weighted difference from target energies\n",
      "-12.71   9.75  10.68  -0.93  -0.49  -0.49 energies\n",
      "cost score: 3.871179048132509\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.16   3.40   0.11   7.01   0.19   0.64 weighted difference from target energies\n",
      "-12.52   9.40  10.89  -1.50  -0.44  -0.36 energies\n",
      "cost score: 3.56243512443232\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.41   3.44   0.70   8.29   0.15   0.46 weighted difference from target energies\n",
      "-11.77   9.44  10.30  -0.85  -0.54  -0.54 energies\n",
      "cost score: 3.6264530683351377\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.18   3.40   0.50   7.80   0.05   0.86 weighted difference from target energies\n",
      "-12.47   9.40  10.50  -1.10  -0.84  -0.14 energies\n",
      "cost score: 3.587051398649781\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.16   4.22  -0.18   8.09  -0.09  -0.26 weighted difference from target energies\n",
      "-13.49  10.22  11.18  -0.96  -1.26  -1.26 energies\n",
      "cost score: 4.26796181210038\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.16   4.09   0.87   9.93  -0.09  -0.28 weighted difference from target energies\n",
      "-12.53  10.09  10.13  -0.04  -1.28  -1.28 energies\n",
      "cost score: 4.173053371841008\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.42   5.33   0.96  12.58   0.08   0.23 weighted difference from target energies\n",
      "-11.73  11.33  10.04   1.29  -0.77  -0.77 energies\n",
      "cost score: 5.359647109870356\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.39   3.40   0.99   8.79  -0.07  -0.20 weighted difference from target energies\n",
      "-17.18   9.40  10.01  -0.60  -1.20  -1.20 energies\n",
      "cost score: 3.548043903962408\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.12   3.81  -0.06   7.48  -0.10  -0.29 weighted difference from target energies\n",
      "-13.37   9.81  11.06  -1.26  -1.29  -1.29 energies\n",
      "cost score: 3.8802598394246846\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.22   4.56  -0.16   8.81  -0.06  -0.18 weighted difference from target energies\n",
      "-12.35  10.56  11.16  -0.60  -1.18  -1.18 energies\n",
      "cost score: 4.603683405866846\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.52   3.61   1.29   9.82   0.06   0.18 weighted difference from target energies\n",
      "-17.57   9.61   9.71  -0.09  -0.82  -0.82 energies\n",
      "cost score: 3.767287900937489\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.48   1.84   4.18  12.06   0.04   0.11 weighted difference from target energies\n",
      "-17.45   7.84   6.82   1.03  -0.89  -0.89 energies\n",
      "cost score: 4.308531241372137\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.55   3.41   1.15   9.13   0.15   0.45 weighted difference from target energies\n",
      "-17.64   9.41   9.85  -0.43  -0.55  -0.55 energies\n",
      "cost score: 3.5948431559972485\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.50   2.17   2.35   9.03   0.06   0.28 weighted difference from target energies\n",
      "-17.50   8.17   8.65  -0.49  -0.81  -0.72 energies\n",
      "cost score: 3.0815018322445966\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.47   6.50  -2.02   8.97   0.09   0.35 weighted difference from target energies\n",
      "-17.41  12.50  13.02  -0.51  -0.73  -0.65 energies\n",
      "cost score: 6.506772428200373\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.45   0.84   3.53   8.74   0.10   0.33 weighted difference from target energies\n",
      "-17.36   6.84   7.47  -0.63  -0.71  -0.67 energies\n",
      "cost score: 3.665342159975815\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.40   0.84   4.04   9.77   0.37   1.86 weighted difference from target energies\n",
      "-17.19   6.84   6.96  -0.11   0.11   0.86 energies\n",
      "cost score: 4.211027011257096\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.40   1.32   2.89   8.42   0.03   0.10 weighted difference from target energies\n",
      "-17.20   7.32   8.11  -0.79  -0.90  -0.90 energies\n",
      "cost score: 3.1828003792526367\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.47   1.32   3.05   8.74  -0.06  -0.18 weighted difference from target energies\n",
      "-17.41   7.32   7.95  -0.63  -1.18  -1.18 energies\n",
      "cost score: 3.2906884193508197\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.87   2.10   0.79   5.77  -0.07   0.18 weighted difference from target energies\n",
      "-15.62   8.10  10.21  -2.11  -1.20  -0.82 energies\n",
      "cost score: 2.5581807303155246\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU ACCAGGCAAUGCCUCAAUGCUCUUGUGCUUCAAAAUUUGUUAUGCUGGGGAAUUGGAAUGGUUGCGAUUGAGGUGGCAGUUAAAUCCUACAUCAGAGCGUAGGGUCCCGGCAGGCUCGUCCUAGCGGGCGCGUCCGGUAGGAGCUGCAGUAUGAGUAAAGGAGAAGAACUUUUCACU 2.5581807303155246\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.52   2.10   1.79   7.78   0.05   1.25 weighted difference from target energies\n",
      "-14.55   8.10   9.21  -1.11  -0.84   0.25 energies\n",
      "cost score: 2.9598331974737375\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.14   2.10   0.16   4.52   0.13   1.09 weighted difference from target energies\n",
      "-12.59   8.10  10.84  -2.74  -0.62   0.09 energies\n",
      "cost score: 2.680434184574008\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.71   2.40   2.31   9.41  -0.05   0.81 weighted difference from target energies\n",
      "-15.14   8.40   8.69  -0.30  -1.15  -0.19 energies\n",
      "cost score: 3.2077874939738695\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.83   3.27   2.38  11.28   0.19   0.57 weighted difference from target energies\n",
      "-15.50   9.27   8.62   0.64  -0.43  -0.43 energies\n",
      "cost score: 3.69840706730955\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.72   4.12   2.87  13.97   0.18   0.53 weighted difference from target energies\n",
      "-15.15  10.12   8.13   1.98  -0.47  -0.47 energies\n",
      "cost score: 4.410042470323551\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.14   4.11   2.08  12.37   0.35   1.05 weighted difference from target energies\n",
      "-12.59  10.11   8.92   1.19   0.05   0.05 energies\n",
      "cost score: 4.309944654997803\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.94   1.74  -0.42   2.63   0.38   1.65 weighted difference from target energies\n",
      "-10.19   7.74  11.42  -3.68   0.13   0.65 energies\n",
      "cost score: 2.744962825827812\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.48   4.65  -0.53   8.24   0.96   3.01 weighted difference from target energies\n",
      " -8.57  10.65  11.53  -0.88   1.87   2.01 energies\n",
      "cost score: 4.882984880765144\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.94   1.74   0.37   4.22   0.38   1.54 weighted difference from target energies\n",
      "-10.19   7.74  10.63  -2.89   0.13   0.54 energies\n",
      "cost score: 2.760717444030748\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.14   1.89   0.31   4.40   0.82   2.49 weighted difference from target energies\n",
      " -9.58   7.89  10.69  -2.80   1.46   1.49 energies\n",
      "cost score: 3.236924566893098\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.94   1.74   0.21   3.90   0.38   1.56 weighted difference from target energies\n",
      "-10.19   7.74  10.79  -3.05   0.13   0.56 energies\n",
      "cost score: 2.753465552006981\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.49   3.80  -1.94   3.73   0.38   2.45 weighted difference from target energies\n",
      "-11.53   9.80  12.94  -3.14   0.13   1.45 energies\n",
      "cost score: 4.088088060037183\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.91   3.09   0.19   6.56   0.55   1.73 weighted difference from target energies\n",
      "-10.26   9.09  10.81  -1.72   0.65   0.73 energies\n",
      "cost score: 3.498076805845664\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.60   1.74  -0.06   3.36   0.38   1.14 weighted difference from target energies\n",
      "-11.20   7.74  11.06  -3.32   0.14   0.14 energies\n",
      "cost score: 2.5689054894753824\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.92   3.04  -2.34   1.39   0.83   2.60 weighted difference from target energies\n",
      " -7.25   9.04  13.34  -4.31   1.50   1.60 energies\n",
      "cost score: 3.7722510520937274\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.60   1.74  -0.68   2.11   0.38   1.14 weighted difference from target energies\n",
      "-11.20   7.74  11.68  -3.94   0.14   0.14 energies\n",
      "cost score: 2.5339487546667687\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU ACCAGGCAAUGCUAUAAUGCUCUGGUGCUUCAGAAUUUGUUAUACGGGGGAAUUGGACUGGUUGCGAUUGAGGUGGCAGCUAAAUCCUACAUCAGAGCGUAGGGUCCCGACAGGCUCGUCCUAGCGGGCGCGUCCGGUAGGAGCUGCUGUAUGAGUAAAGGAGAAGAACUUUUCACU 2.5339487546667687\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.59   1.74  -0.67   2.14   0.38   1.13 weighted difference from target energies\n",
      "-11.22   7.74  11.67  -3.93   0.13   0.13 energies\n",
      "cost score: 2.5335986318579073\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU ACCAGGCAAUGCUAUAAUGCUCUGGUGCUUCAGAAUUUGUUAUACGGGGGAAUUGGACUGGUUGCGAUCGAGGUGGCAGCUAAAUCCUACAUCAGAGCGUAGGGUCCCGACAGGCUCGUCCUAGCGGGCGCGUCCGGUAGGAGCUGCUGUAUGAGUAAAGGAGAAGAACUUUUCACU 2.5335986318579073\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.46   3.89   1.62  11.02   0.42   1.25 weighted difference from target energies\n",
      "-11.62   9.89   9.38   0.51   0.25   0.25 energies\n",
      "cost score: 4.103502379940986\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.17   4.04  -1.33   5.43   0.38   1.14 weighted difference from target energies\n",
      "-13.50  10.04  12.33  -2.28   0.14   0.14 energies\n",
      "cost score: 4.138015631100835\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.59   1.74  -0.59   2.30   0.38   1.13 weighted difference from target energies\n",
      "-11.22   7.74  11.59  -3.85   0.13   0.13 energies\n",
      "cost score: 2.5369539568837274\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.14  -1.22  -2.38  -7.21   1.04   4.89 weighted difference from target energies\n",
      " -6.59   4.78  13.38  -8.60   2.11   3.89 energies\n",
      "cost score: 4.974192805805231\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.51   2.71  -0.83   3.76   0.38   1.13 weighted difference from target energies\n",
      "-11.48   8.71  11.83  -3.12   0.13   0.13 energies\n",
      "cost score: 3.07953891953067\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.58   1.55  -0.97   1.16   0.37   1.12 weighted difference from target energies\n",
      "-11.26   7.55  11.97  -4.42   0.12   0.12 energies\n",
      "cost score: 2.4320847864345025\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU ACCAGGCAAUGCGAUAAUGCUGUGGUGCUUCAGAAUUUGUUAUACGGGGGAAUUGGACUGGUUGCGAUCGAGGUGGCAGCUAAAUCCUACAUCAGAGCGUAGGGUCCCGACAGGCUCGUCCUAGCGGGCGCGUCCGGUAGGAGCUGCUGUAUGAGUAAAGGAGAAGAACUUUUCACU 2.4320847864345025\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.42   2.31  -0.16   4.29   0.37   1.11 weighted difference from target energies\n",
      "-11.74   8.31  11.16  -2.86   0.11   0.11 energies\n",
      "cost score: 2.82692056394309\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.89   2.97  -1.48   2.99   0.38   1.39 weighted difference from target energies\n",
      "-10.34   8.97  12.48  -3.50   0.13   0.39 energies\n",
      "cost score: 3.320785804375774\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.54   3.14  -1.03   4.23   0.38   2.21 weighted difference from target energies\n",
      "-11.39   9.14  12.03  -2.88   0.14   1.21 energies\n",
      "cost score: 3.5770064662021293\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.49   3.23  -0.47   5.52   0.38   1.61 weighted difference from target energies\n",
      "-11.52   9.23  11.47  -2.24   0.14   0.61 energies\n",
      "cost score: 3.5272416763163825\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.93   1.53  -0.93   1.20   0.38   1.71 weighted difference from target energies\n",
      "-10.22   7.53  11.93  -4.40   0.14   0.71 energies\n",
      "cost score: 2.6773199853446714\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.85   1.77  -1.38   0.79   0.38   1.55 weighted difference from target energies\n",
      "-10.46   7.77  12.38  -4.61   0.13   0.55 energies\n",
      "cost score: 2.683913386707155\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.36   1.76  -0.40   2.72   0.32   0.99 weighted difference from target energies\n",
      "-11.92   7.76  11.40  -3.64  -0.03  -0.01 energies\n",
      "cost score: 2.4843136194836215\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.03   2.25   0.76   6.03   0.43   1.28 weighted difference from target energies\n",
      "-13.10   8.25  10.24  -1.99   0.28   0.28 energies\n",
      "cost score: 2.876172732413802\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.65   1.75  -0.68   2.13   0.32   0.95 weighted difference from target energies\n",
      "-11.04   7.75  11.68  -3.94  -0.05  -0.05 energies\n",
      "cost score: 2.4956282822772575\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.53   4.16  -0.52   7.28   0.32   0.96 weighted difference from target energies\n",
      "-11.41  10.16  11.52  -1.36  -0.04  -0.04 energies\n",
      "cost score: 4.249359265958139\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.30   3.20  -0.95   4.48   0.32   0.95 weighted difference from target energies\n",
      "-12.09   9.20  11.95  -2.76  -0.05  -0.05 energies\n",
      "cost score: 3.4048310455729727\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.08   1.76  -0.00   3.52   0.38   1.15 weighted difference from target energies\n",
      "-12.76   7.76  11.00  -3.24   0.15   0.15 energies\n",
      "cost score: 2.5274255004812933\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.29   4.68   1.73  12.82   0.47   1.41 weighted difference from target energies\n",
      "-13.88  10.68   9.27   1.41   0.41   0.41 energies\n",
      "cost score: 4.789408597183069\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.12   1.57  -0.04   3.06   0.38   1.15 weighted difference from target energies\n",
      "-12.63   7.57  11.04  -3.47   0.15   0.15 energies\n",
      "cost score: 2.4441765046115207\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.44   1.57   1.41   5.96   0.38   1.14 weighted difference from target energies\n",
      "-11.69   7.57   9.59  -2.02   0.14   0.14 energies\n",
      "cost score: 2.7108559773424066\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.39   1.55   1.50   6.10   0.38   1.15 weighted difference from target energies\n",
      "-11.82   7.55   9.50  -1.95   0.15   0.15 energies\n",
      "cost score: 2.7277475862112457\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.08   3.43   2.92  12.70   0.31   0.94 weighted difference from target energies\n",
      "-13.25   9.43   8.08   1.35  -0.06  -0.06 energies\n",
      "cost score: 3.9942966756856535\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.20   3.85   0.02   7.75   0.41   1.24 weighted difference from target energies\n",
      "-12.39   9.85  10.98  -1.13   0.24   0.24 energies\n",
      "cost score: 3.9957549322946964\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.40   3.42   0.37   7.58   0.42   1.25 weighted difference from target energies\n",
      "-11.80   9.42  10.63  -1.21   0.25   0.25 energies\n",
      "cost score: 3.6507900258907635\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.41   3.32   1.07   8.77   0.41   1.24 weighted difference from target energies\n",
      "-11.76   9.32   9.93  -0.61   0.24   0.24 energies\n",
      "cost score: 3.609267903401072\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.49   3.20   1.09   8.59   0.40   1.20 weighted difference from target energies\n",
      "-11.54   9.20   9.91  -0.71   0.20   0.20 energies\n",
      "cost score: 3.5244726706759097\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.79   3.26   2.68  11.87   0.09   0.59 weighted difference from target energies\n",
      "-10.63   9.26   8.32   0.94  -0.73  -0.41 energies\n",
      "cost score: 3.8214043196837166\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.56   4.53   2.63  14.32   0.06   0.18 weighted difference from target energies\n",
      " -8.32  10.53   8.37   2.16  -0.82  -0.82 energies\n",
      "cost score: 4.733754123854691\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.94   4.08   2.63  13.42   0.06   0.18 weighted difference from target energies\n",
      " -7.19  10.08   8.37   1.71  -0.82  -0.82 energies\n",
      "cost score: 4.410034073832813\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.96   4.10   0.55   9.30   0.07   0.20 weighted difference from target energies\n",
      " -7.11  10.10  10.45  -0.35  -0.80  -0.80 energies\n",
      "cost score: 4.2715001347752155\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.08   5.88   0.43  12.63   0.07   0.21 weighted difference from target energies\n",
      " -6.76  11.88  10.57   1.31  -0.79  -0.79 energies\n",
      "cost score: 5.915231115001284\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.50   4.64   0.55  10.37   0.07   0.20 weighted difference from target energies\n",
      " -8.50  10.64  10.45   0.19  -0.80  -0.80 energies\n",
      "cost score: 4.718474617191159\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.25   7.71   0.56  16.53   0.01   0.02 weighted difference from target energies\n",
      "-12.26  13.71  10.44   3.27  -0.98  -0.98 energies\n",
      "cost score: 7.7073541112470805\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.87   4.21   0.81  10.05   0.08   0.24 weighted difference from target energies\n",
      " -7.38  10.21  10.19   0.03  -0.76  -0.76 energies\n",
      "cost score: 4.36477870744923\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.89   5.83   0.81  13.28   0.08   0.25 weighted difference from target energies\n",
      " -7.32  11.83  10.19   1.64  -0.75  -0.75 energies\n",
      "cost score: 5.857950592978841\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.87   4.63   0.81  10.89   0.08   0.24 weighted difference from target energies\n",
      " -7.38  10.63  10.19   0.45  -0.76  -0.76 energies\n",
      "cost score: 4.735363990633097\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.09   0.39   1.32   3.42   0.11   0.34 weighted difference from target energies\n",
      " -6.72   6.39   9.68  -3.29  -0.66  -0.66 energies\n",
      "cost score: 2.7637380784064787\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.91   3.53   1.00   9.07   0.20   0.61 weighted difference from target energies\n",
      " -7.26   9.53  10.00  -0.46  -0.39  -0.39 energies\n",
      "cost score: 3.8456549099138853\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.15   0.36   3.78   8.27   0.06   0.18 weighted difference from target energies\n",
      " -6.55   6.36   7.22  -0.86  -0.82  -0.82 energies\n",
      "cost score: 4.026766651006139\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.56   4.61   1.33  11.89   0.08   0.23 weighted difference from target energies\n",
      " -8.32  10.61   9.67   0.95  -0.77  -0.77 energies\n",
      "cost score: 4.717181140861299\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.70   1.47   1.35   5.65   0.03   0.21 weighted difference from target energies\n",
      " -7.91   7.47   9.65  -2.17  -0.90  -0.79 energies\n",
      "cost score: 2.76955300133045\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.90   5.95   1.04  13.99   0.07   0.57 weighted difference from target energies\n",
      " -7.31  11.95   9.96   1.99  -0.78  -0.43 energies\n",
      "cost score: 5.986069765014179\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.65   4.25   0.76  10.00   0.01   0.04 weighted difference from target energies\n",
      " -5.05  10.25  10.24   0.00  -0.96  -0.96 energies\n",
      "cost score: 4.478782057184117\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.83   3.23  -1.68   3.11  -0.05  -0.15 weighted difference from target energies\n",
      " -7.50   9.23  12.68  -3.45  -1.15  -1.15 energies\n",
      "cost score: 3.511048015341167\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.11   1.79  -0.22   3.15   0.01   0.04 weighted difference from target energies\n",
      " -6.66   7.79  11.22  -3.43  -0.96  -0.96 energies\n",
      "cost score: 2.8407019474158295\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.11   4.61  -0.23   8.76   0.07   0.21 weighted difference from target energies\n",
      " -6.66  10.61  11.23  -0.62  -0.79  -0.79 energies\n",
      "cost score: 4.713970088845677\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.25   4.11  -0.22   7.78   0.07   0.20 weighted difference from target energies\n",
      " -6.25  10.11  11.22  -1.11  -0.80  -0.80 energies\n",
      "cost score: 4.30173009393986\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.06   1.44  -0.04   2.81   0.14   0.41 weighted difference from target energies\n",
      " -6.83   7.44  11.04  -3.60  -0.59  -0.59 energies\n",
      "cost score: 2.7515277973449344\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.64   1.17   1.50   5.34   0.18   0.54 weighted difference from target energies\n",
      " -8.09   7.17   9.50  -2.33  -0.46  -0.46 energies\n",
      "cost score: 2.7571326192760823\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.19   1.19  -0.47   1.43   0.15   0.45 weighted difference from target energies\n",
      " -6.43   7.19  11.47  -4.28  -0.55  -0.55 energies\n",
      "cost score: 2.7454913148168387\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.41   1.19  -0.30   1.77   0.06   0.19 weighted difference from target energies\n",
      " -5.76   7.19  11.30  -4.12  -0.83  -0.81 energies\n",
      "cost score: 2.8598572468419254\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.22   3.16  -2.37   1.59   0.13   0.40 weighted difference from target energies\n",
      " -6.35   9.16  13.37  -4.20  -0.60  -0.60 energies\n",
      "cost score: 3.571287948579246\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.03   0.19   0.38   1.16   0.17   0.51 weighted difference from target energies\n",
      " -6.91   6.19  10.62  -4.42  -0.49  -0.49 energies\n",
      "cost score: 2.576164960431397\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.79   0.14   1.15   2.58   0.17   0.52 weighted difference from target energies\n",
      " -7.62   6.14   9.85  -3.71  -0.48  -0.48 energies\n",
      "cost score: 2.579306584040439\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.49   0.80   0.54   2.69   0.36   1.07 weighted difference from target energies\n",
      " -5.53   6.80  10.46  -3.65   0.07   0.07 energies\n",
      "cost score: 3.013409689386426\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.56   4.31   1.15  10.93   0.16   0.48 weighted difference from target energies\n",
      " -8.33  10.31   9.85   0.47  -0.52  -0.52 energies\n",
      "cost score: 4.447454264798854\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.29   0.30   1.15   2.90  -0.09   0.31 weighted difference from target energies\n",
      " -6.14   6.30   9.85  -3.55  -1.26  -0.69 energies\n",
      "cost score: 2.8116071642608707\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.45   4.01   0.96   9.94  -0.13  -0.38 weighted difference from target energies\n",
      " -5.65  10.01  10.04  -0.03  -1.38  -1.38 energies\n",
      "cost score: 4.262613422650936\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.31   0.19   1.17   2.72  -0.10   0.27 weighted difference from target energies\n",
      " -6.06   6.19   9.83  -3.64  -1.29  -0.73 energies\n",
      "cost score: 2.8189313022516225\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.13   3.05   1.17   8.44  -0.10   0.26 weighted difference from target energies\n",
      " -6.62   9.05   9.83  -0.78  -1.29  -0.74 energies\n",
      "cost score: 3.5515911028344664\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.44   3.78   1.22   9.99  -0.14  -0.41 weighted difference from target energies\n",
      " -5.68   9.78   9.78  -0.01  -1.41  -1.41 energies\n",
      "cost score: 4.095616001908815\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.81   0.06   1.17   2.45   0.17   0.51 weighted difference from target energies\n",
      " -7.56   6.06   9.83  -3.77  -0.49  -0.49 energies\n",
      "cost score: 2.5844958413172856\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.83   0.64   1.17   3.61   0.17   0.52 weighted difference from target energies\n",
      " -7.52   6.64   9.83  -3.20  -0.48  -0.48 energies\n",
      "cost score: 2.652070781391555\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.29   0.63   1.48   4.22   0.15   0.45 weighted difference from target energies\n",
      " -6.13   6.63   9.52  -2.89  -0.55  -0.55 energies\n",
      "cost score: 2.9372629582863445\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.32  -0.40   1.83   2.84   0.58   1.74 weighted difference from target energies\n",
      " -9.04   5.60   9.17  -3.58   0.74   0.74 energies\n",
      "cost score: 2.8960560126486237\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.73   1.49   1.50   5.98   0.52   1.55 weighted difference from target energies\n",
      " -7.81   7.49   9.50  -2.01   0.55   0.55 energies\n",
      "cost score: 3.0419545760351987\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.11   3.27   1.64   9.82   0.56   1.69 weighted difference from target energies\n",
      " -6.67   9.27   9.36  -0.09   0.69   0.69 energies\n",
      "cost score: 3.8469527490459416\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.66   4.99   2.37  14.72   0.16   0.49 weighted difference from target energies\n",
      "-11.01  10.99   8.63   2.36  -0.51  -0.51 energies\n",
      "cost score: 5.090352007952686\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.03   4.46   2.92  14.75  -0.13  -0.38 weighted difference from target energies\n",
      " -9.91  10.46   8.08   2.37  -1.38  -1.38 energies\n",
      "cost score: 4.693729689748857\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.98   3.99   3.28  14.54   0.00   0.01 weighted difference from target energies\n",
      "-10.07   9.99   7.72   2.27  -0.99  -0.99 energies\n",
      "cost score: 4.446646099446061\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.36  -0.25   3.59   6.67  -0.28  -0.58 weighted difference from target energies\n",
      "-11.92   5.75   7.41  -1.67  -1.84  -1.58 energies\n",
      "cost score: 3.681231127277635\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.84  -0.11   3.86   7.51   0.13   0.38 weighted difference from target energies\n",
      "-10.49   5.89   7.14  -1.24  -0.62  -0.62 energies\n",
      "cost score: 3.9788970725458945\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.25  -0.29   2.87   5.18  -0.40  -0.77 weighted difference from target energies\n",
      "-12.26   5.71   8.13  -2.41  -2.19  -1.77 energies\n",
      "cost score: 3.0388263872676986\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.71  -0.29   5.89  11.21  -0.57  -1.72 weighted difference from target energies\n",
      "-10.86   5.71   5.11   0.61  -2.72  -2.72 energies\n",
      "cost score: 5.904266091472314\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.52   3.59   3.90  14.98  -0.18  -0.55 weighted difference from target energies\n",
      "-14.57   9.59   7.10   2.49  -1.55  -1.55 energies\n",
      "cost score: 4.473656457567463\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.09   2.88   3.88  13.53   0.06   0.19 weighted difference from target energies\n",
      "-13.26   8.88   7.12   1.76  -0.81  -0.81 energies\n",
      "cost score: 4.241608798055261\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.50   2.87   3.86  13.45  -0.16  -0.49 weighted difference from target energies\n",
      "-14.51   8.87   7.14   1.73  -1.49  -1.49 energies\n",
      "cost score: 4.205988535562947\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.46   3.57   3.72  14.57  -0.15  -0.46 weighted difference from target energies\n",
      "-14.39   9.57   7.28   2.29  -1.46  -1.46 energies\n",
      "cost score: 4.365691557393463\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.50   3.68   3.77  14.90  -0.17  -0.51 weighted difference from target energies\n",
      "-14.51   9.68   7.23   2.45  -1.51  -1.51 energies\n",
      "cost score: 4.443795023292701\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.50   3.67   3.76  14.86  -0.17  -0.51 weighted difference from target energies\n",
      "-14.50   9.67   7.24   2.43  -1.51  -1.51 energies\n",
      "cost score: 4.434617408745016\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.43  -1.13   1.64   1.01  -0.42  -0.70 weighted difference from target energies\n",
      "-11.71   4.87   9.36  -4.49  -2.26  -1.70 energies\n",
      "cost score: 2.099199380555982\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU ACCACAUUAUGGGAUAAUACCGCGGUGCUUCAGAAUUCGUUAUACGGGGGGAUUGGACUGGGUGCGAGUGACGUAGCUUUAAAAACUUCCAUCUGUGCGGAGUGUACCGACUGCCUUCGUCUAGCAGCCGCAUCCGGUAGGAGCUACUGUAUGAGUAAAGGAGAAGAACUUUUCACU 2.099199380555982\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.43  -1.13   1.70   1.12  -0.42  -0.74 weighted difference from target energies\n",
      "-11.70   4.87   9.30  -4.44  -2.26  -1.74 energies\n",
      "cost score: 2.133707822475161\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.42  -1.15   1.08  -0.14  -0.43  -0.41 weighted difference from target energies\n",
      "-11.74   4.85   9.92  -5.07  -2.30  -1.41 energies\n",
      "cost score: 1.807937193816747\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU ACCACAUUAUGGGAUAAUACCGCGGUGCUUCAGAAUUCGUUAUACGGGGGGAUUGGACUGGGUGCGAGUGACGUAGCUUUAAAAACUUCCAACUGUGCGGAGUGUACCGACUGGCUUCGUCUAGCAGCCGCAUCCGGUAGGAGCUACUGUAUGAGUAAAGGAGAAGAACUUUUCACU 1.807937193816747\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.46  -1.13   0.90  -0.46  -0.44  -0.13 weighted difference from target energies\n",
      "-11.63   4.87  10.10  -5.23  -2.33  -1.13 energies\n",
      "cost score: 1.7725026388162064\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU ACCACAUGAUGGGAUAAUACCGCGGUGCUUCAGAAUUCGUUAUACGGGGGGAUUGGACUGGGUGCGAGUGACGUAGCUUUAAAAACUUCCAACUGUGCGGAGUGUACCGACUGGCUUCGUCUAGCAGCCGCAUCCGGUAGGAGCUACUGUAUGAGUAAAGGAGAAGAACUUUUCACU 1.7725026388162064\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.15  -0.61   2.68   4.15  -0.44  -0.24 weighted difference from target energies\n",
      "-12.56   5.39   8.32  -2.93  -2.32  -1.24 energies\n",
      "cost score: 2.87801448666802\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.36  -1.01   1.14   0.25  -0.42  -0.66 weighted difference from target energies\n",
      "-11.93   4.99   9.86  -4.88  -2.25  -1.66 energies\n",
      "cost score: 1.8048907746499285\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.36  -1.01   1.12   0.23  -0.42  -0.52 weighted difference from target energies\n",
      "-11.93   4.99   9.88  -4.89  -2.26  -1.52 energies\n",
      "cost score: 1.8121485902716619\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.34  -1.07   0.53  -1.08  -0.40  -0.58 weighted difference from target energies\n",
      "-11.97   4.93  10.47  -5.54  -2.20  -1.58 energies\n",
      "cost score: 1.5439178204178152\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU ACGACAUGAUGGGUUAAUACCGCGGUGCUUCAGAAUUCGUUAUACGGGGGGAUUGGACUGGGUGCGAGUGACGUAGCUUUAAAAACUUCGAACUGUGCGGAGUGUACCGACUGGCUUCGUCUAGCAGCCGCAUCCGGUAGGAGCUACUGUAUGAGUAAAGGAGAAGAACUUUUCACU 1.5439178204178152\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.34  -1.07   0.53  -1.07  -0.40  -0.61 weighted difference from target energies\n",
      "-11.97   4.93  10.47  -5.54  -2.20  -1.61 energies\n",
      "cost score: 1.5410893127448906\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU ACGACAUGAUGGGUUAAUACCGCGGUGCUUCAGAAUUCGUUAUACGGGGGGAUUGGACUGGGUGCGAGUGACGUAGCUUUAAAAAUUUCGAACUGUGCGGAGUGUACCGACUGGCUUCGUCUAGCAGCCGCAUCCGGUAGGAGCUACUGUAUGAGUAAAGGAGAAGAACUUUUCACU 1.5410893127448906\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.34  -1.07   0.53  -1.07  -0.40  -0.60 weighted difference from target energies\n",
      "-11.97   4.93  10.47  -5.54  -2.20  -1.60 energies\n",
      "cost score: 1.542268897973359\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.34  -1.07   0.53  -1.08  -0.40  -0.58 weighted difference from target energies\n",
      "-11.97   4.93  10.47  -5.54  -2.20  -1.58 energies\n",
      "cost score: 1.5440540320852596\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.17  -0.37   3.80   6.86  -0.56  -1.29 weighted difference from target energies\n",
      "-12.49   5.63   7.20  -1.57  -2.68  -2.29 energies\n",
      "cost score: 3.859456095728671\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.31  -0.86   0.78  -0.16  -0.39  -0.73 weighted difference from target energies\n",
      "-12.08   5.14  10.22  -5.08  -2.17  -1.73 energies\n",
      "cost score: 1.6330864003968175\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.34  -1.07   0.53  -1.08  -0.40  -0.58 weighted difference from target energies\n",
      "-11.97   4.93  10.47  -5.54  -2.20  -1.58 energies\n",
      "cost score: 1.5438650530232532\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.34  -1.09   0.57  -1.04  -0.41  -0.61 weighted difference from target energies\n",
      "-11.99   4.91  10.43  -5.52  -2.24  -1.61 energies\n",
      "cost score: 1.549159637752079\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.01  -1.14   1.98   1.67   0.02   1.29 weighted difference from target energies\n",
      " -9.96   4.86   9.02  -4.16  -0.93   0.29 energies\n",
      "cost score: 2.7057995023498336\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.98  -1.04   2.26   2.44   0.02   1.21 weighted difference from target energies\n",
      "-10.07   4.96   8.74  -3.78  -0.95   0.21 energies\n",
      "cost score: 2.8333995365796696\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.01  -0.95   2.10   2.29  -0.40  -1.13 weighted difference from target energies\n",
      " -9.98   5.05   8.90  -3.86  -2.21  -2.13 energies\n",
      "cost score: 2.5050325757317227\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.91   0.37   1.51   3.76  -0.24  -0.72 weighted difference from target energies\n",
      "-10.26   6.37   9.49  -3.12  -1.72  -1.72 energies\n",
      "cost score: 2.2745659663731987\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.38   1.27   1.76   6.06  -0.37  -1.10 weighted difference from target energies\n",
      "-11.85   7.27   9.24  -1.97  -2.10  -2.10 energies\n",
      "cost score: 2.474114255330601\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.17   2.48   1.24   7.44  -0.49  -1.46 weighted difference from target energies\n",
      "-12.48   8.48   9.76  -1.28  -2.46  -2.46 energies\n",
      "cost score: 2.856869184936527\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.51   1.11   1.55   5.32  -0.34  -1.03 weighted difference from target energies\n",
      "-11.46   7.11   9.45  -2.34  -2.03  -2.03 energies\n",
      "cost score: 2.3506041185792803\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.24   2.04   0.08   4.23  -0.44  -0.62 weighted difference from target energies\n",
      " -9.27   8.04  10.92  -2.88  -2.33  -1.62 energies\n",
      "cost score: 2.5950513493909657\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.95  -0.92   2.22   2.60  -0.16  -0.29 weighted difference from target energies\n",
      "-10.15   5.08   8.78  -3.70  -1.47  -1.29 energies\n",
      "cost score: 2.6224847150959856\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.11  -1.03   2.20   2.34   0.12   0.71 weighted difference from target energies\n",
      " -9.67   4.97   8.80  -3.83  -0.65  -0.29 energies\n",
      "cost score: 2.746668870738011\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.77  -0.36   2.19   3.67  -0.44  -1.31 weighted difference from target energies\n",
      "-10.68   5.64   8.81  -3.17  -2.32  -2.31 energies\n",
      "cost score: 2.545204434447301\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.78   0.07   5.31  10.76  -0.16  -0.49 weighted difference from target energies\n",
      "-15.34   6.07   5.69   0.38  -1.49  -1.49 energies\n",
      "cost score: 5.327196827304161\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.68  -0.07   1.24   2.33  -0.44  -1.32 weighted difference from target energies\n",
      "-10.96   5.93   9.76  -3.83  -2.32  -2.32 energies\n",
      "cost score: 1.9828123631900598\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.49  -0.07   1.94   3.75   0.37   1.11 weighted difference from target energies\n",
      " -8.53   5.93   9.06  -3.13   0.11   0.11 energies\n",
      "cost score: 2.8232708906522577\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.13   0.80  -0.34   0.92   0.28   0.83 weighted difference from target energies\n",
      " -9.60   6.80  11.34  -4.54  -0.17  -0.17 energies\n",
      "cost score: 2.2680042439943504\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.14   0.78  -0.31   0.94   0.28   0.83 weighted difference from target energies\n",
      " -9.59   6.78  11.31  -4.53  -0.17  -0.17 energies\n",
      "cost score: 2.2670132572917914\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.04   0.83  -0.32   1.01   0.27   0.81 weighted difference from target energies\n",
      " -9.89   6.83  11.32  -4.49  -0.19  -0.19 energies\n",
      "cost score: 2.2399159565177014\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.30   0.54  -0.74  -0.39   0.28   0.84 weighted difference from target energies\n",
      " -9.10   6.54  11.74  -5.20  -0.16  -0.16 energies\n",
      "cost score: 2.252075496065899\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.34   0.43  -0.73  -0.59   0.28   0.84 weighted difference from target energies\n",
      " -8.98   6.43  11.73  -5.29  -0.16  -0.16 energies\n",
      "cost score: 2.2494120417184718\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.92   1.79  -0.50   2.58   0.30   0.89 weighted difference from target energies\n",
      "-10.24   7.79  11.50  -3.71  -0.11  -0.11 energies\n",
      "cost score: 2.555998502156954\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.96   2.82  -0.13   5.37   0.46   1.39 weighted difference from target energies\n",
      "-10.11   8.82  11.13  -2.32   0.39   0.39 energies\n",
      "cost score: 3.251315848812186\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.13   1.05  -0.57   0.96   0.27   0.81 weighted difference from target energies\n",
      " -9.61   7.05  11.57  -4.52  -0.19  -0.19 energies\n",
      "cost score: 2.309407276727578\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.24   1.05   0.21   2.51   0.28   0.84 weighted difference from target energies\n",
      " -9.27   7.05  10.79  -3.75  -0.16  -0.16 energies\n",
      "cost score: 2.4146489035851344\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.53   1.05   0.76   3.61   0.42   1.26 weighted difference from target energies\n",
      "-11.40   7.05  10.24  -3.19   0.25   0.26 energies\n",
      "cost score: 2.462217913217511\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.37  -0.91   2.29   2.75   0.38   1.15 weighted difference from target energies\n",
      "-11.88   5.09   8.71  -3.63   0.15   0.15 energies\n",
      "cost score: 2.7919300223438084\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.21  -0.91   1.66   1.48   0.22   0.65 weighted difference from target energies\n",
      "-12.37   5.09   9.34  -4.26  -0.35  -0.35 energies\n",
      "cost score: 2.3052899582253605\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.38   2.42  -0.89   3.07   0.27   0.80 weighted difference from target energies\n",
      "-11.87   8.42  11.89  -3.47  -0.20  -0.20 energies\n",
      "cost score: 2.8146773452276914\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.81   2.42  -0.73   3.39   0.01   0.04 weighted difference from target energies\n",
      "-10.58   8.42  11.73  -3.30  -0.96  -0.96 energies\n",
      "cost score: 2.7767165322443947\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.33   3.75   0.00   7.51  -0.08  -0.25 weighted difference from target energies\n",
      "-12.02   9.75  11.00  -1.25  -1.25  -1.25 energies\n",
      "cost score: 3.8432221882263176\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.82   5.11  -1.29   7.63   0.02   0.07 weighted difference from target energies\n",
      "-10.53  11.11  12.29  -1.18  -0.93  -0.93 energies\n",
      "cost score: 5.134945402569208\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.83   1.81  -0.20   3.21   0.23   0.68 weighted difference from target energies\n",
      "-10.51   7.81  11.20  -3.39  -0.32  -0.32 energies\n",
      "cost score: 2.5198613027524823\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.37   1.72   0.01   3.45   0.30   1.44 weighted difference from target energies\n",
      " -8.89   7.72  10.99  -3.27  -0.09   0.44 energies\n",
      "cost score: 2.7787699065964357\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.72   2.79   0.02   5.61  -0.07  -0.21 weighted difference from target energies\n",
      "-10.85   8.79  10.98  -2.19  -1.21  -1.21 energies\n",
      "cost score: 3.047339092034572\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.72   2.79   0.02   5.61  -0.07  -0.21 weighted difference from target energies\n",
      "-10.85   8.79  10.98  -2.19  -1.21  -1.21 energies\n",
      "cost score: 3.047339092034572\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.69   2.85   0.04   5.78  -0.05  -0.11 weighted difference from target energies\n",
      "-10.94   8.85  10.96  -2.11  -1.15  -1.11 energies\n",
      "cost score: 3.096780534380813\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.95   2.81  -0.05   5.51  -0.06   0.28 weighted difference from target energies\n",
      "-10.15   8.81  11.05  -2.24  -1.18  -0.72 energies\n",
      "cost score: 3.1092626996496953\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.27   3.31  -0.13   6.35  -0.05   1.19 weighted difference from target energies\n",
      " -9.20   9.31  11.13  -1.82  -1.16   0.19 energies\n",
      "cost score: 3.583570167345291\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.04   1.96   0.15   4.24   0.16   0.47 weighted difference from target energies\n",
      " -9.89   7.96  10.85  -2.88  -0.53  -0.53 energies\n",
      "cost score: 2.631060717984757\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.13   3.07   0.03   6.21   0.17   0.67 weighted difference from target energies\n",
      " -9.60   9.07  10.97  -1.90  -0.49  -0.33 energies\n",
      "cost score: 3.3611991890059256\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.36   2.83   0.18   6.00   0.31   1.36 weighted difference from target energies\n",
      " -8.91   8.83  10.82  -2.00  -0.08   0.36 energies\n",
      "cost score: 3.304875810754473\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.44   2.67   0.24   5.82   0.30   1.52 weighted difference from target energies\n",
      " -8.67   8.67  10.76  -2.09  -0.11   0.52 energies\n",
      "cost score: 3.2530815703526827\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.27   2.28   0.29   5.13   0.28   1.00 weighted difference from target energies\n",
      " -9.18   8.28  10.71  -2.44  -0.15   0.00 energies\n",
      "cost score: 2.929057310818745\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.31   2.63   0.82   6.89   0.14   1.18 weighted difference from target energies\n",
      " -9.06   8.63  10.18  -1.55  -0.59   0.18 energies\n",
      "cost score: 3.1869355891777253\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.35   2.58   0.83   6.83   0.15   1.64 weighted difference from target energies\n",
      " -8.95   8.58  10.17  -1.58  -0.56   0.64 energies\n",
      "cost score: 3.246832730770663\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.42   3.87   0.74   9.22   0.17   1.69 weighted difference from target energies\n",
      " -8.73   9.87  10.26  -0.39  -0.49   0.69 energies\n",
      "cost score: 4.109682852676716\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.62   1.86   0.94   5.59  -0.22  -0.51 weighted difference from target energies\n",
      "-11.13   7.86  10.06  -2.20  -1.66  -1.51 energies\n",
      "cost score: 2.5037017333745863\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.04   2.23   1.07   6.60  -0.07   0.86 weighted difference from target energies\n",
      " -9.88   8.23   9.93  -1.70  -1.22  -0.14 energies\n",
      "cost score: 2.9089692196521884\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.12   2.13   1.10   6.46  -0.42  -1.26 weighted difference from target energies\n",
      "-12.63   8.13   9.90  -1.77  -2.26  -2.26 energies\n",
      "cost score: 2.6017256938992657\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.00   2.30   1.28   7.16  -0.51  -1.53 weighted difference from target energies\n",
      "-12.99   8.30   9.72  -1.42  -2.53  -2.53 energies\n",
      "cost score: 2.7340802189310094\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.65   2.22   0.89   6.22  -0.22  -0.58 weighted difference from target energies\n",
      "-11.04   8.22  10.11  -1.89  -1.65  -1.58 energies\n",
      "cost score: 2.7017865090902307\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.70   2.74   0.30   6.09  -0.08  -0.23 weighted difference from target energies\n",
      "-10.90   8.74  10.70  -1.96  -1.24  -1.23 energies\n",
      "cost score: 3.0248246978512263\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.97   2.74  -0.11   5.25  -0.28  -0.51 weighted difference from target energies\n",
      "-10.09   8.74  11.11  -2.37  -1.84  -1.51 energies\n",
      "cost score: 3.0151086830822584\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.95   2.75   0.26   6.01  -0.31  -0.53 weighted difference from target energies\n",
      "-10.14   8.75  10.74  -1.99  -1.92  -1.53 energies\n",
      "cost score: 3.035960569493764\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.28   3.97  -0.65   6.65  -0.10  -0.06 weighted difference from target energies\n",
      " -9.16   9.97  11.65  -1.68  -1.30  -1.06 energies\n",
      "cost score: 4.078014054564675\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.28   3.55  -1.18   4.73   0.07   0.65 weighted difference from target energies\n",
      " -9.15   9.55  12.18  -2.63  -0.79  -0.35 energies\n",
      "cost score: 3.7301678146179076\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.43   3.24  -1.43   3.62   0.16   0.74 weighted difference from target energies\n",
      " -8.70   9.24  12.43  -3.19  -0.52  -0.26 energies\n",
      "cost score: 3.501440245274393\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.43   3.01  -1.20   3.63   0.21   0.92 weighted difference from target energies\n",
      " -8.70   9.01  12.20  -3.18  -0.37  -0.08 energies\n",
      "cost score: 3.354091369806682\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.47   2.52  -1.05   2.94   0.12   0.52 weighted difference from target energies\n",
      " -8.59   8.52  12.05  -3.53  -0.63  -0.48 energies\n",
      "cost score: 2.9919256852073994\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.30   3.79  -1.40   4.79   0.23   1.08 weighted difference from target energies\n",
      " -9.10   9.79  12.40  -2.61  -0.31   0.08 energies\n",
      "cost score: 3.9605569978700097\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.91   4.56  -1.49   6.14   0.61   2.55 weighted difference from target energies\n",
      " -7.26  10.56  12.49  -1.93   0.83   1.55 energies\n",
      "cost score: 4.763450894716235\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.48   5.04  -0.52   9.03   0.40   1.60 weighted difference from target energies\n",
      " -8.56  11.04  11.52  -0.48   0.19   0.60 energies\n",
      "cost score: 5.109654677732463\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.40   5.04  -0.51   9.05   0.47   2.04 weighted difference from target energies\n",
      " -8.80  11.04  11.51  -0.47   0.42   1.04 energies\n",
      "cost score: 5.124785029053869\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.67   5.95  -0.95   9.99   1.01   3.29 weighted difference from target energies\n",
      " -8.00  11.95  11.95  -0.00   2.04   2.29 energies\n",
      "cost score: 6.0362120500372765\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.19   5.03  -0.41   9.24   0.20   1.37 weighted difference from target energies\n",
      " -9.44  11.03  11.41  -0.38  -0.39   0.37 energies\n",
      "cost score: 5.084756925976794\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.34   6.64  -1.45  10.38   0.27   2.32 weighted difference from target energies\n",
      " -8.99  12.64  12.45   0.19  -0.18   1.32 energies\n",
      "cost score: 6.662457388279089\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.76   4.75  -0.50   8.50  -0.14  -0.06 weighted difference from target energies\n",
      "-10.71  10.75  11.50  -0.75  -1.43  -1.06 energies\n",
      "cost score: 4.7899769953351115\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.54   5.49  -0.49  10.02  -0.10  -0.15 weighted difference from target energies\n",
      "-11.38  11.49  11.49   0.01  -1.29  -1.15 energies\n",
      "cost score: 5.510235361982399\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.69   3.77   0.31   8.17   0.37   1.11 weighted difference from target energies\n",
      "-10.93   9.77  10.69  -0.92   0.11   0.11 energies\n",
      "cost score: 3.9367344899589005\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.01   5.96  -0.29  11.34  -0.32  -0.97 weighted difference from target energies\n",
      "-13.04  11.96  11.29   0.67  -1.97  -1.97 energies\n",
      "cost score: 5.96940586907572\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.78   4.42   2.00  12.83  -0.08   0.10 weighted difference from target energies\n",
      "-10.67  10.42   9.00   1.41  -1.23  -0.90 energies\n",
      "cost score: 4.546680253004772\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.79   3.30   0.70   7.99  -0.26  -0.07 weighted difference from target energies\n",
      "-10.64   9.30  10.30  -1.00  -1.77  -1.07 energies\n",
      "cost score: 3.497401604055659\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.80   3.36  -0.19   6.34  -0.24  -0.12 weighted difference from target energies\n",
      "-10.59   9.36  11.19  -1.83  -1.73  -1.12 energies\n",
      "cost score: 3.5134240803413896\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.25   1.95  -0.11   3.68   0.08   0.82 weighted difference from target energies\n",
      " -9.26   7.95  11.11  -3.16  -0.75  -0.18 energies\n",
      "cost score: 2.6913199734316584\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.10   2.38  -0.12   4.53   0.04   0.70 weighted difference from target energies\n",
      " -9.69   8.38  11.12  -2.73  -0.88  -0.30 energies\n",
      "cost score: 2.879373833577792\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.25   6.27  -1.37   9.80  -0.18  -0.44 weighted difference from target energies\n",
      "-12.25  12.27  12.37  -0.10  -1.54  -1.44 energies\n",
      "cost score: 6.274760901950771\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.22   2.42  -0.30   4.25   0.14   0.88 weighted difference from target energies\n",
      " -9.33   8.42  11.30  -2.88  -0.58  -0.12 energies\n",
      "cost score: 2.942605897863807\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.55   4.79  -0.61   8.37  -0.19  -0.19 weighted difference from target energies\n",
      "-11.34  10.79  11.61  -0.82  -1.57  -1.19 energies\n",
      "cost score: 4.82566441355284\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.21   2.49  -0.27   4.44   0.03   1.01 weighted difference from target energies\n",
      " -9.36   8.49  11.27  -2.78  -0.91   0.01 energies\n",
      "cost score: 2.991180509974928\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.38   4.29  -2.56   3.46  -0.10   0.59 weighted difference from target energies\n",
      " -8.87  10.29  13.56  -3.27  -1.31  -0.41 energies\n",
      "cost score: 4.377775328867652\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.52   4.31  -2.41   3.80  -0.05   1.03 weighted difference from target energies\n",
      " -8.45  10.31  13.41  -3.10  -1.16   0.03 energies\n",
      "cost score: 4.416055523105488\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.43   5.95  -2.25   7.40   0.24   1.32 weighted difference from target energies\n",
      " -8.71  11.95  13.25  -1.30  -0.28   0.32 energies\n",
      "cost score: 5.97287392040657\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.86   4.31  -2.01   4.61   0.48   5.06 weighted difference from target energies\n",
      " -4.42  10.31  13.01  -2.70   0.43   4.06 energies\n",
      "cost score: 5.526132715694805\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.46   4.48  -2.42   4.13  -0.06   1.02 weighted difference from target energies\n",
      " -8.63  10.48  13.42  -2.93  -1.17   0.02 energies\n",
      "cost score: 4.572233519450534\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.21   5.75  -2.43   6.63  -0.04   0.70 weighted difference from target energies\n",
      " -9.38  11.75  13.43  -1.68  -1.11  -0.30 energies\n",
      "cost score: 5.769774844515174\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.09   2.46  -1.18   2.55   0.59   2.00 weighted difference from target energies\n",
      " -6.73   8.46  12.18  -3.72   0.78   1.00 energies\n",
      "cost score: 3.377344756906191\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.90   2.36  -0.74   3.23   0.46   1.55 weighted difference from target energies\n",
      " -7.29   8.36  11.74  -3.38   0.39   0.55 energies\n",
      "cost score: 3.180358841094654\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.19   5.52  -1.58   7.88   0.53   1.65 weighted difference from target energies\n",
      " -9.44  11.52  12.58  -1.06   0.60   0.65 energies\n",
      "cost score: 5.559353741723021\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.41   5.29  -3.69   3.20  -0.28   0.38 weighted difference from target energies\n",
      " -8.78  11.29  14.69  -3.40  -1.84  -0.62 energies\n",
      "cost score: 5.322639536552489\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.93   6.04  -2.97   6.13   0.31   0.92 weighted difference from target energies\n",
      " -7.20  12.04  13.97  -1.93  -0.08  -0.08 energies\n",
      "cost score: 6.065961130783585\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.53   4.46  -1.64   5.66   0.72   2.24 weighted difference from target energies\n",
      " -8.42  10.46  12.64  -2.17   1.15   1.24 energies\n",
      "cost score: 4.634231511528753\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.50   4.99  -1.86   6.26   0.67   2.49 weighted difference from target energies\n",
      " -8.50  10.99  12.86  -1.87   1.01   1.49 energies\n",
      "cost score: 5.107625000122005\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.55   3.55  -0.78   5.53   0.51   1.55 weighted difference from target energies\n",
      " -8.35   9.55  11.78  -2.23   0.53   0.55 energies\n",
      "cost score: 3.835427790811298\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  3.05   4.45  -0.73   7.44   0.61   4.62 weighted difference from target energies\n",
      " -3.84  10.45  11.73  -1.28   0.83   3.62 energies\n",
      "cost score: 5.349637065403371\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.62   3.92  -1.59   4.65  -0.22   0.58 weighted difference from target energies\n",
      " -8.14   9.92  12.59  -2.68  -1.65  -0.42 energies\n",
      "cost score: 4.061021461920715\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.00   3.51  -1.11   4.81  -0.26   0.34 weighted difference from target energies\n",
      "-10.00   9.51  12.11  -2.60  -1.78  -0.66 energies\n",
      "cost score: 3.6546739562996864\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.00   3.51  -1.10   4.82  -0.26   0.34 weighted difference from target energies\n",
      "-10.01   9.51  12.10  -2.59  -1.78  -0.66 energies\n",
      "cost score: 3.6551789605426213\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.20   3.53  -1.65   3.76  -0.17   0.67 weighted difference from target energies\n",
      " -9.39   9.53  12.65  -3.12  -1.50  -0.33 energies\n",
      "cost score: 3.7031939050095533\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.25   3.52  -1.74   3.54  -0.09   0.96 weighted difference from target energies\n",
      " -9.24   9.52  12.74  -3.23  -1.26  -0.04 energies\n",
      "cost score: 3.710292469780767\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.50   3.52  -2.10   2.84  -0.25   0.44 weighted difference from target energies\n",
      " -8.50   9.52  13.10  -3.58  -1.75  -0.56 energies\n",
      "cost score: 3.708880154079145\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.88   3.52  -2.50   2.05   0.09   1.26 weighted difference from target energies\n",
      " -7.36   9.52  13.50  -3.98  -0.72   0.26 energies\n",
      "cost score: 3.809576141200955\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.38   3.99  -0.93   6.12  -0.13   0.70 weighted difference from target energies\n",
      " -5.86   9.99  11.93  -1.94  -1.39  -0.30 energies\n",
      "cost score: 4.223979774150484\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.66   5.14  -1.90   6.47  -0.48   0.64 weighted difference from target energies\n",
      " -5.02  11.14  12.90  -1.77  -2.44  -0.36 energies\n",
      "cost score: 5.233156194961957\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.50   3.52  -1.28   4.48   0.14   0.74 weighted difference from target energies\n",
      " -5.49   9.52  12.28  -2.76  -0.59  -0.26 energies\n",
      "cost score: 3.905852244420752\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.73   6.99  -3.46   7.05   0.40   2.13 weighted difference from target energies\n",
      " -4.80  12.99  14.46  -1.47   0.20   1.13 energies\n",
      "cost score: 7.010436162966738\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.92   2.83  -3.41  -1.15  -0.38   0.89 weighted difference from target energies\n",
      " -4.25   8.83  14.41  -5.58  -2.13  -0.11 energies\n",
      "cost score: 3.653533247108757\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.50   3.52  -1.28   4.48   0.14   0.74 weighted difference from target energies\n",
      " -5.49   9.52  12.28  -2.76  -0.59  -0.26 energies\n",
      "cost score: 3.905852244420752\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.09   3.57  -1.13   4.89   0.63   1.93 weighted difference from target energies\n",
      " -6.74   9.57  12.13  -2.55   0.90   0.93 energies\n",
      "cost score: 3.9655127630476334\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.68   5.60  -0.41  10.38   0.08   0.99 weighted difference from target energies\n",
      " -7.95  11.60  11.41   0.19  -0.75  -0.01 energies\n",
      "cost score: 5.634361864100573\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.07   5.49  -1.84   7.30   0.75   2.38 weighted difference from target energies\n",
      " -6.79  11.49  12.84  -1.35   1.25   1.38 energies\n",
      "cost score: 5.574483355256657\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.50   5.91  -2.22   7.38   0.42   1.85 weighted difference from target energies\n",
      " -8.50  11.91  13.22  -1.31   0.25   0.85 energies\n",
      "cost score: 5.947823005635743\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.82   3.22  -1.01   4.44   0.58   1.80 weighted difference from target energies\n",
      " -7.55   9.22  12.01  -2.78   0.73   0.80 energies\n",
      "cost score: 3.6753923130469675\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.88   4.20  -1.60   5.19  -0.05   1.66 weighted difference from target energies\n",
      " -7.37  10.20  12.60  -2.40  -1.14   0.66 energies\n",
      "cost score: 4.373792741274781\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.59   4.42  -1.15   6.55   0.07   1.79 weighted difference from target energies\n",
      " -8.24  10.42  12.15  -1.72  -0.79   0.79 energies\n",
      "cost score: 4.559096426499443\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.91   2.96  -1.26   3.41   0.61   2.01 weighted difference from target energies\n",
      " -7.26   8.96  12.26  -3.29   0.84   1.01 energies\n",
      "cost score: 3.575844267098564\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.36   5.32  -0.18  10.29   0.07   1.58 weighted difference from target energies\n",
      " -8.93  11.32  11.18   0.15  -0.79   0.58 energies\n",
      "cost score: 5.372792988937243\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.20   2.04  -1.30   1.49   0.61   2.02 weighted difference from target energies\n",
      " -6.41   8.04  12.30  -4.26   0.84   1.02 energies\n",
      "cost score: 3.27118884262065\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.43   2.04  -1.20   1.69   0.81   2.71 weighted difference from target energies\n",
      " -5.72   8.04  12.20  -4.16   1.43   1.71 energies\n",
      "cost score: 3.5997698316386404\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.94   2.04  -1.21   1.65   0.00   1.39 weighted difference from target energies\n",
      " -7.19   8.04  12.21  -4.17  -0.99   0.39 energies\n",
      "cost score: 2.992742661800688\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.65   2.96  -1.14   3.64   0.01   1.41 weighted difference from target energies\n",
      " -8.04   8.96  12.14  -3.18  -0.98   0.41 energies\n",
      "cost score: 3.4012208043852885\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.76   5.22  -1.26   7.93   0.14   1.29 weighted difference from target energies\n",
      " -4.71  11.22  12.26  -1.04  -0.58   0.29 energies\n",
      "cost score: 5.328987006061868\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.46   4.21  -1.72   4.98   0.14   1.97 weighted difference from target energies\n",
      " -8.61  10.21  12.72  -2.51  -0.57   0.97 energies\n",
      "cost score: 4.383346604571402\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.00   4.04  -3.92   0.25   0.30   2.34 weighted difference from target energies\n",
      " -7.01  10.04  14.92  -4.88  -0.10   1.34 energies\n",
      "cost score: 4.333428551624626\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.69   2.74  -2.24   1.02   0.32   1.35 weighted difference from target energies\n",
      " -7.92   8.74  13.24  -4.49  -0.05   0.35 energies\n",
      "cost score: 3.2704448234720482\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.34   3.98  -1.08   5.81   0.30   1.11 weighted difference from target energies\n",
      " -8.98   9.98  12.08  -2.09  -0.10   0.11 energies\n",
      "cost score: 4.131761401504677\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.06   4.99  -1.63   6.72   0.08   0.50 weighted difference from target energies\n",
      " -9.82  10.99  12.63  -1.64  -0.77  -0.50 energies\n",
      "cost score: 5.027437798965857\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.74   4.98  -0.73   8.50  -0.22  -0.21 weighted difference from target energies\n",
      "-10.77  10.98  11.73  -0.75  -1.65  -1.21 energies\n",
      "cost score: 5.011462748932606\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.73   4.98  -0.77   8.41  -0.23  -0.23 weighted difference from target energies\n",
      "-10.80  10.98  11.77  -0.79  -1.68  -1.23 energies\n",
      "cost score: 5.0051651673508\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.85   5.11  -1.10   8.01  -0.12   0.09 weighted difference from target energies\n",
      "-10.46  11.11  12.10  -1.00  -1.35  -0.91 energies\n",
      "cost score: 5.1348759265756\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.80   5.11  -1.03   8.16  -0.16  -0.04 weighted difference from target energies\n",
      "-10.59  11.11  12.03  -0.92  -1.48  -1.04 energies\n",
      "cost score: 5.132920508867582\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.81   5.11  -1.04   8.14  -0.16  -0.03 weighted difference from target energies\n",
      "-10.58  11.11  12.04  -0.93  -1.48  -1.03 energies\n",
      "cost score: 5.133205772891824\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.16   5.63  -2.04   7.17   0.18   0.97 weighted difference from target energies\n",
      " -9.51  11.63  13.04  -1.42  -0.45  -0.03 energies\n",
      "cost score: 5.651974767701883\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.82   5.11  -1.08   8.05  -0.15   0.01 weighted difference from target energies\n",
      "-10.54  11.11  12.08  -0.97  -1.44  -0.99 energies\n",
      "cost score: 5.136408967416745\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.81   5.11  -1.06   8.09  -0.15  -0.01 weighted difference from target energies\n",
      "-10.56  11.11  12.06  -0.95  -1.46  -1.01 energies\n",
      "cost score: 5.137395229081522\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.20   5.32  -1.86   6.91   0.13   0.85 weighted difference from target energies\n",
      " -9.40  11.32  12.86  -1.54  -0.61  -0.15 energies\n",
      "cost score: 5.348642252690581\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.11   5.92  -1.84   8.17   0.39   1.83 weighted difference from target energies\n",
      " -9.67  11.92  12.84  -0.91   0.17   0.83 energies\n",
      "cost score: 5.951982860078382\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.03   5.18  -1.71   6.94   0.02   0.48 weighted difference from target energies\n",
      " -9.92  11.18  12.71  -1.53  -0.95  -0.52 energies\n",
      "cost score: 5.215129752780701\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.23   5.29  -1.96   6.66   0.16   0.95 weighted difference from target energies\n",
      " -9.30  11.29  12.96  -1.67  -0.52  -0.05 energies\n",
      "cost score: 5.325316387522568\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.15   5.09  -1.88   6.42   0.09   0.69 weighted difference from target energies\n",
      " -9.54  11.09  12.88  -1.79  -0.73  -0.31 energies\n",
      "cost score: 5.126352022830105\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.16   4.85  -1.22   7.28   0.40   2.85 weighted difference from target energies\n",
      " -9.53  10.85  12.22  -1.36   0.21   1.85 energies\n",
      "cost score: 5.014099105147066\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.15   4.59  -0.97   7.23   0.46   2.89 weighted difference from target energies\n",
      " -9.56  10.59  11.97  -1.38   0.37   1.89 energies\n",
      "cost score: 4.799060247284666\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.90   4.48  -0.14   8.68   0.21   2.12 weighted difference from target energies\n",
      "-10.29  10.48  11.14  -0.66  -0.37   1.12 energies\n",
      "cost score: 4.614218315805871\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.73   4.66   0.17   9.67   0.23   1.83 weighted difference from target energies\n",
      "-10.80  10.66  10.83  -0.17  -0.32   0.83 energies\n",
      "cost score: 4.760270168363569\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.15   5.23   0.32  11.08   0.28   1.87 weighted difference from target energies\n",
      " -9.54  11.23  10.68   0.54  -0.16   0.87 energies\n",
      "cost score: 5.290469496747679\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.21   6.12  -0.74  10.75   0.64   2.51 weighted difference from target energies\n",
      " -9.38  12.12  11.74   0.38   0.93   1.51 energies\n",
      "cost score: 6.159315587528747\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.36   6.92  -1.69  10.47   0.24   2.72 weighted difference from target energies\n",
      " -8.91  12.92  12.69   0.23  -0.27   1.72 energies\n",
      "cost score: 6.943137990085651\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.98   5.23  -1.20   8.05   0.90   2.98 weighted difference from target energies\n",
      " -7.05  11.23  12.20  -0.97   1.69   1.98 energies\n",
      "cost score: 5.374321782814652\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.98   5.23  -1.20   8.05   0.90   2.98 weighted difference from target energies\n",
      " -7.05  11.23  12.20  -0.97   1.69   1.98 energies\n",
      "cost score: 5.374230698158092\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.98   5.22  -1.26   7.93   0.90   3.01 weighted difference from target energies\n",
      " -7.05  11.22  12.26  -1.04   1.69   2.01 energies\n",
      "cost score: 5.371146083894851\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.40   9.69  -3.97  11.44   1.00   3.12 weighted difference from target energies\n",
      " -8.79  15.69  14.97   0.72   2.01   2.12 energies\n",
      "cost score: 9.687413154867022\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.99   5.19  -1.25   7.88   0.90   3.03 weighted difference from target energies\n",
      " -7.03  11.19  12.25  -1.06   1.69   2.03 energies\n",
      "cost score: 5.347253037166501\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.10   5.50  -1.55   7.90   0.90   3.34 weighted difference from target energies\n",
      " -6.71  11.50  12.55  -1.05   1.69   2.34 energies\n",
      "cost score: 5.647829066567787\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.26   5.19  -0.47   9.43   0.83   3.84 weighted difference from target energies\n",
      " -6.22  11.19  11.47  -0.28   1.50   2.84 energies\n",
      "cost score: 5.473579842817317\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.27   5.25  -0.53   9.43   0.84   3.85 weighted difference from target energies\n",
      " -6.18  11.25  11.53  -0.28   1.51   2.85 energies\n",
      "cost score: 5.5183610722828\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.45   8.47  -1.71  13.52  -0.13   3.59 weighted difference from target energies\n",
      " -5.66  14.47  12.71   1.76  -1.40   2.59 energies\n",
      "cost score: 8.475306956796366\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.24   3.95  -1.17   5.55   0.89   3.37 weighted difference from target energies\n",
      " -6.27   9.95  12.17  -2.23   1.66   2.37 energies\n",
      "cost score: 4.5326355566746575\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.54   4.65  -0.61   8.08   0.27   4.77 weighted difference from target energies\n",
      " -5.38  10.65  11.61  -0.96  -0.20   3.77 energies\n",
      "cost score: 5.466676643591742\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.87   4.57   0.40   9.93  -0.80  -2.39 weighted difference from target energies\n",
      " -4.40  10.57  10.60  -0.03  -3.39  -3.39 energies\n",
      "cost score: 4.751778187175069\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.93   4.29   0.60   9.79   0.61   2.90 weighted difference from target energies\n",
      " -7.22  10.29  10.40  -0.11   0.84   1.90 energies\n",
      "cost score: 4.6240659473368915\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.41   5.99  -2.14   7.70  -0.10  -0.02 weighted difference from target energies\n",
      " -8.78  11.99  13.14  -1.15  -1.31  -1.02 energies\n",
      "cost score: 6.0028748922943205\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.06   4.49   0.48   9.94   0.46   4.17 weighted difference from target energies\n",
      " -6.83  10.49  10.52  -0.03   0.39   3.17 energies\n",
      "cost score: 5.107717726993581\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.96   4.31   0.50   9.60   0.65   2.97 weighted difference from target energies\n",
      " -7.13  10.31  10.50  -0.20   0.94   1.97 energies\n",
      "cost score: 4.646355348088294\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.86   4.72   0.26   9.95  -0.80  -2.39 weighted difference from target energies\n",
      " -4.41  10.72  10.74  -0.03  -3.39  -3.39 energies\n",
      "cost score: 4.878762518418813\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.85   8.74  -3.68  10.12  -0.81  -2.42 weighted difference from target energies\n",
      " -4.44  14.74  14.68   0.06  -3.42  -3.42 energies\n",
      "cost score: 8.746998236979323\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.82   4.65   0.19   9.68   0.89   2.94 weighted difference from target energies\n",
      " -7.55  10.65  10.81  -0.16   1.68   1.94 energies\n",
      "cost score: 4.89256934523593\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.81   4.65   0.21   9.72   0.86   2.92 weighted difference from target energies\n",
      " -7.57  10.65  10.79  -0.14   1.58   1.92 energies\n",
      "cost score: 4.889278895807556\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.89   4.72  -0.06   9.32   0.90   2.87 weighted difference from target energies\n",
      " -7.32  10.72  11.06  -0.34   1.69   1.87 energies\n",
      "cost score: 4.941571277848007\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.11   7.52  -0.91  13.22   0.67   2.30 weighted difference from target energies\n",
      " -6.66  13.52  11.91   1.61   1.00   1.30 energies\n",
      "cost score: 7.533859620545771\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.46   4.67  -1.07   7.21   0.51   1.86 weighted difference from target energies\n",
      " -8.62  10.67  12.07  -1.39   0.52   0.86 energies\n",
      "cost score: 4.785715563851711\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.61   5.78  -2.10   7.37   0.66   1.97 weighted difference from target energies\n",
      " -8.16  11.78  13.10  -1.31   0.97   0.97 energies\n",
      "cost score: 5.82635010727073\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.53   6.28  -1.32   9.93   0.49   1.75 weighted difference from target energies\n",
      " -8.42  12.28  12.32  -0.04   0.46   0.75 energies\n",
      "cost score: 6.301056521151648\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.70   4.67  -1.05   7.24   0.82   2.57 weighted difference from target energies\n",
      " -7.90  10.67  12.05  -1.38   1.47   1.57 energies\n",
      "cost score: 4.854260117488339\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.09   3.87  -0.56   6.62   0.54   2.95 weighted difference from target energies\n",
      " -9.73   9.87  11.56  -1.69   0.61   1.95 energies\n",
      "cost score: 4.28320409536861\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.52   6.33  -2.80   7.05   0.84   3.50 weighted difference from target energies\n",
      " -8.45  12.33  13.80  -1.47   1.51   2.50 energies\n",
      "cost score: 6.3973867795699935\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.23   2.57   0.19   5.52   0.81   3.14 weighted difference from target energies\n",
      " -9.32   8.57  10.81  -2.24   1.44   2.14 energies\n",
      "cost score: 3.7616126224908304\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.93   5.65  -0.96   9.40   0.83   2.80 weighted difference from target energies\n",
      "-10.22  11.65  11.96  -0.30   1.48   1.80 energies\n",
      "cost score: 5.726717270896488\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.71   7.29  -0.13  14.33   0.82   2.56 weighted difference from target energies\n",
      "-10.86  13.29  11.13   2.17   1.47   1.56 energies\n",
      "cost score: 7.305393464540747\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.07   5.34  -1.84   7.00   0.80   2.99 weighted difference from target energies\n",
      " -9.79  11.34  12.84  -1.50   1.41   1.99 energies\n",
      "cost score: 5.451190886418489\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.85   6.29  -0.64  11.30   0.50   2.35 weighted difference from target energies\n",
      "-10.44  12.29  11.64   0.65   0.49   1.35 energies\n",
      "cost score: 6.317421795472403\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.07   5.20  -1.70   6.99   0.81   2.98 weighted difference from target energies\n",
      " -9.78  11.20  12.70  -1.51   1.44   1.98 energies\n",
      "cost score: 5.326211314398476\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.83   5.58  -0.91   9.34   0.40   1.70 weighted difference from target energies\n",
      "-10.52  11.58  11.91  -0.33   0.21   0.70 energies\n",
      "cost score: 5.620060910082766\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.93   6.98  -0.60  12.77   0.46   1.39 weighted difference from target energies\n",
      "-10.22  12.98  11.60   1.38   0.39   0.39 energies\n",
      "cost score: 6.9861158453996826\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.66   5.73  -2.38   6.70   0.44   2.89 weighted difference from target energies\n",
      " -8.03  11.73  13.38  -1.65   0.32   1.89 energies\n",
      "cost score: 5.809711254862879\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.17   5.58  -2.21   6.76   0.76   4.46 weighted difference from target energies\n",
      " -6.49  11.58  13.21  -1.62   1.27   3.46 energies\n",
      "cost score: 5.896295073657511\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.12   5.11  -2.65   4.92   0.89   4.25 weighted difference from target energies\n",
      " -6.65  11.11  13.65  -2.54   1.66   3.25 energies\n",
      "cost score: 5.507056531080377\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.33   6.99  -6.51   0.95   1.26   3.93 weighted difference from target energies\n",
      " -6.02  12.99  17.51  -4.53   2.78   2.93 energies\n",
      "cost score: 7.043204141982159\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.31   7.58  -7.66  -0.16   0.83   3.90 weighted difference from target energies\n",
      " -6.07  13.58  18.66  -5.08   1.50   2.90 energies\n",
      "cost score: 7.607234464105577\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.41   8.13  -5.95   4.36   0.68   3.46 weighted difference from target energies\n",
      " -5.76  14.13  16.95  -2.82   1.04   2.46 energies\n",
      "cost score: 8.139520626233566\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.99   9.85  -6.93   5.83   0.52   2.58 weighted difference from target energies\n",
      " -7.02  15.85  17.93  -2.08   0.56   1.58 energies\n",
      "cost score: 9.850769763352048\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.70   5.94  -2.23   7.42   0.92   3.11 weighted difference from target energies\n",
      " -7.91  11.94  13.23  -1.29   1.77   2.11 energies\n",
      "cost score: 6.013735438158964\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.85   7.21  -2.30   9.82  -1.75  -5.26 weighted difference from target energies\n",
      " -7.46  13.21  13.30  -0.09  -6.26  -6.26 energies\n",
      "cost score: 7.211852976018537\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.91   4.95  -1.93   6.06   1.05   3.29 weighted difference from target energies\n",
      " -7.26  10.95  12.93  -1.97   2.14   2.29 energies\n",
      "cost score: 5.182984769958493\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.86   4.99  -1.09   7.81   1.01   3.33 weighted difference from target energies\n",
      " -7.43  10.99  12.09  -1.10   2.03   2.33 energies\n",
      "cost score: 5.220773582694209\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.07   4.99  -1.38   7.23   0.32   3.79 weighted difference from target energies\n",
      " -6.79  10.99  12.38  -1.39  -0.04   2.79 energies\n",
      "cost score: 5.305616896601743\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.28   5.86  -1.90   7.91   0.86   3.89 weighted difference from target energies\n",
      " -6.17  11.86  12.90  -1.04   1.59   2.89 energies\n",
      "cost score: 6.017297829422546\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.54   6.23  -2.88   6.69   0.89   4.10 weighted difference from target energies\n",
      " -5.37  12.23  13.88  -1.65   1.67   3.10 energies\n",
      "cost score: 6.369053372220084\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.74   6.15  -2.25   7.80   0.71   2.88 weighted difference from target energies\n",
      " -7.79  12.15  13.25  -1.10   1.12   1.88 energies\n",
      "cost score: 6.207530959882982\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.99   6.76  -2.45   8.63   0.78   2.64 weighted difference from target energies\n",
      " -7.02  12.76  13.45  -0.69   1.33   1.64 energies\n",
      "cost score: 6.790670856220152\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.76   5.49  -3.05   4.88   0.78   2.66 weighted difference from target energies\n",
      "-10.73  11.49  14.05  -2.56   1.35   1.66 energies\n",
      "cost score: 5.560459927043883\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.98   5.49  -3.01   4.95   0.71   3.01 weighted difference from target energies\n",
      "-10.07  11.49  14.01  -2.53   1.14   2.01 energies\n",
      "cost score: 5.584666963785996\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.85   6.32  -1.75   9.13   0.76   3.11 weighted difference from target energies\n",
      "-10.45  12.32  12.75  -0.44   1.28   2.11 energies\n",
      "cost score: 6.363799195153204\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.99   5.49  -1.96   7.05   0.71   3.03 weighted difference from target energies\n",
      "-10.02  11.49  12.96  -1.47   1.14   2.03 energies\n",
      "cost score: 5.587750449763167\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.00   5.49  -3.52   3.93  -0.28   0.05 weighted difference from target energies\n",
      "-13.01  11.49  14.52  -3.04  -1.85  -0.95 energies\n",
      "cost score: 5.498747384928226\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.08   5.58  -3.32   4.52  -0.42  -0.45 weighted difference from target energies\n",
      "-12.76  11.58  14.32  -2.74  -2.26  -1.45 energies\n",
      "cost score: 5.5860423568739686\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.81   5.42  -3.84   3.16  -0.00   2.45 weighted difference from target energies\n",
      "-10.57  11.42  14.84  -3.42  -1.01   1.45 energies\n",
      "cost score: 5.479256904822422\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.73   6.08  -2.89   6.37   0.00   2.32 weighted difference from target energies\n",
      "-10.81  12.08  13.89  -1.82  -1.00   1.32 energies\n",
      "cost score: 6.105532007550987\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.81   7.75  -4.97   5.57  -0.00   2.20 weighted difference from target energies\n",
      "-10.58  13.75  15.97  -2.21  -1.01   1.20 energies\n",
      "cost score: 7.759223061384694\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.89   5.42  -3.86   3.11  -0.00   2.47 weighted difference from target energies\n",
      "-10.33  11.42  14.86  -3.44  -1.01   1.47 energies\n",
      "cost score: 5.481363147433613\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.67   4.47  -3.45   2.04  -0.00   2.34 weighted difference from target energies\n",
      " -7.98  10.47  14.45  -3.98  -1.01   1.34 energies\n",
      "cost score: 4.648676992903177\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.67   4.48  -3.45   2.04  -0.00   2.35 weighted difference from target energies\n",
      " -7.98  10.48  14.45  -3.98  -1.01   1.35 energies\n",
      "cost score: 4.651082028877972\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.80   6.37  -3.76   5.23  -0.00   2.08 weighted difference from target energies\n",
      " -7.61  12.37  14.76  -2.38  -1.01   1.08 energies\n",
      "cost score: 6.398600912910353\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.67   4.48  -3.45   2.05  -0.00   2.35 weighted difference from target energies\n",
      " -7.98  10.48  14.45  -3.97  -1.01   1.35 energies\n",
      "cost score: 4.651198574178366\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.67   4.48  -3.45   2.05  -0.00   2.35 weighted difference from target energies\n",
      " -7.98  10.48  14.45  -3.97  -1.01   1.35 energies\n",
      "cost score: 4.6510289301251655\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.74   4.33  -2.91   2.84  -0.01   2.37 weighted difference from target energies\n",
      " -7.79  10.33  13.91  -3.58  -1.02   1.37 energies\n",
      "cost score: 4.535461045894218\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.75   4.46  -2.46   4.00  -0.02   2.71 weighted difference from target energies\n",
      " -7.76  10.46  13.46  -3.00  -1.05   1.71 energies\n",
      "cost score: 4.682525968063145\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.17   3.43  -0.32   6.21   0.00   0.88 weighted difference from target energies\n",
      " -9.48   9.43  11.32  -1.89  -0.99  -0.12 energies\n",
      "cost score: 3.6437108932471642\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.33   4.24  -0.97   6.53  -0.01   4.47 weighted difference from target energies\n",
      " -6.00  10.24  11.97  -1.73  -1.04   3.47 energies\n",
      "cost score: 5.125554463596075\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.92   3.48   0.03   7.03  -0.12   3.16 weighted difference from target energies\n",
      " -7.25   9.48  10.97  -1.49  -1.35   2.16 energies\n",
      "cost score: 4.171331660706115\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.49   3.37   0.34   7.43  -0.16   1.74 weighted difference from target energies\n",
      " -8.52   9.37  10.66  -1.28  -1.48   0.74 energies\n",
      "cost score: 3.7276028654475066\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.38   3.79   0.46   8.49   0.18   1.40 weighted difference from target energies\n",
      " -8.87   9.79  10.54  -0.76  -0.45   0.40 energies\n",
      "cost score: 4.005829335191988\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.94   3.44  -0.42   6.04   0.29   1.44 weighted difference from target energies\n",
      " -7.18   9.44  11.42  -1.98  -0.14   0.44 energies\n",
      "cost score: 3.789695729394513\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.03   4.12  -0.34   7.56  -0.20   0.91 weighted difference from target energies\n",
      " -6.90  10.12  11.34  -1.22  -1.59  -0.09 energies\n",
      "cost score: 4.29142190575217\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.77   4.11   0.71   9.64   0.33   1.28 weighted difference from target energies\n",
      " -7.70  10.11  10.29  -0.18   0.00   0.28 energies\n",
      "cost score: 4.302778845503818\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.43   4.95   0.06  10.02  -0.33   0.18 weighted difference from target energies\n",
      " -8.70  10.95  10.94   0.01  -2.00  -0.82 energies\n",
      "cost score: 5.004074439342257\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.47   4.28   0.61   9.79  -0.31   0.08 weighted difference from target energies\n",
      " -8.59  10.28  10.39  -0.11  -1.92  -0.92 energies\n",
      "cost score: 4.389194086866578\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.98   3.61   0.59   8.42  -0.30   0.04 weighted difference from target energies\n",
      " -7.05   9.61  10.41  -0.79  -1.89  -0.96 energies\n",
      "cost score: 3.871210810951299\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.30   3.43   0.58   8.01  -0.46  -0.16 weighted difference from target energies\n",
      " -6.11   9.43  10.42  -0.99  -2.39  -1.16 energies\n",
      "cost score: 3.785516779280559\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.34   4.23   0.58   9.61  -0.32   0.38 weighted difference from target energies\n",
      " -5.97  10.23  10.42  -0.19  -1.95  -0.62 energies\n",
      "cost score: 4.419625154488715\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.91   4.60   0.68  10.55  -0.46  -0.31 weighted difference from target energies\n",
      " -7.28  10.60  10.32   0.28  -2.39  -1.31 energies\n",
      "cost score: 4.696354399274489\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.74   4.42   0.69  10.21  -0.55  -0.53 weighted difference from target energies\n",
      " -7.78  10.42  10.31   0.11  -2.64  -1.53 energies\n",
      "cost score: 4.518624968471885\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.36   4.43   0.64  10.14   0.02   0.50 weighted difference from target energies\n",
      " -8.92  10.43  10.36   0.07  -0.93  -0.50 energies\n",
      "cost score: 4.526626011070258\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.36   1.39   4.35  11.47   0.17   1.14 weighted difference from target energies\n",
      " -8.91   7.39   6.65   0.74  -0.50   0.14 energies\n",
      "cost score: 4.492631315792243\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.22   5.87   2.66  17.07   0.01   0.78 weighted difference from target energies\n",
      "-12.34  11.87   8.34   3.53  -0.98  -0.22 energies\n",
      "cost score: 5.92582410070667\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.97   0.96   2.84   7.60   0.70   2.65 weighted difference from target energies\n",
      "-10.08   6.96   8.16  -1.20   1.09   1.65 energies\n",
      "cost score: 3.650084645395182\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.04   5.03   1.95  13.96   0.02   2.61 weighted difference from target energies\n",
      "-13.13  11.03   9.05   1.98  -0.94   1.61 energies\n",
      "cost score: 5.169780447291553\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.17   1.38   1.67   6.10   0.13   2.20 weighted difference from target energies\n",
      " -9.49   7.38   9.33  -1.95  -0.60   1.20 energies\n",
      "cost score: 3.1207393072354903\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.46   1.38   3.42   9.60   0.33   3.06 weighted difference from target energies\n",
      " -8.62   7.38   7.58  -0.20  -0.01   2.06 energies\n",
      "cost score: 4.120939414842235\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.13   4.97   3.52  16.98   0.27   3.17 weighted difference from target energies\n",
      "-12.62  10.97   7.48   3.49  -0.18   2.17 energies\n",
      "cost score: 5.317881712729231\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.47   5.06   4.91  19.95   0.30   2.78 weighted difference from target energies\n",
      "-11.58  11.06   6.09   4.98  -0.11   1.78 energies\n",
      "cost score: 5.747023444191692\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.24   5.12   2.83  15.91   0.30   3.01 weighted difference from target energies\n",
      "-12.27  11.12   8.17   2.96  -0.09   2.01 energies\n",
      "cost score: 5.337017463548882\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.71   3.14   2.64  11.55   0.34   2.78 weighted difference from target energies\n",
      " -7.86   9.14   8.36   0.77   0.03   1.78 energies\n",
      "cost score: 4.095494945705834\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.75   3.11   2.54  11.30   0.32   2.84 weighted difference from target energies\n",
      " -7.74   9.11   8.46   0.65  -0.04   1.84 energies\n",
      "cost score: 4.084572416895298\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.84   2.96   2.69  11.28   0.36   2.79 weighted difference from target energies\n",
      " -7.47   8.96   8.31   0.64   0.08   1.79 energies\n",
      "cost score: 4.059130252892589\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.71   5.11   4.18  18.59   0.25   2.68 weighted difference from target energies\n",
      "-10.87  11.11   6.82   4.30  -0.25   1.68 energies\n",
      "cost score: 5.5200450707118165\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.15  -0.02   4.08   8.12   0.20   1.99 weighted difference from target energies\n",
      " -6.55   5.98   6.92  -0.94  -0.39   0.99 energies\n",
      "cost score: 4.349826454484778\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.89  -0.03   2.60   5.13  -0.03   2.72 weighted difference from target energies\n",
      " -7.32   5.97   8.40  -2.43  -1.10   1.72 energies\n",
      "cost score: 3.61544752691936\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.45   0.57   3.81   8.75   0.17   4.15 weighted difference from target energies\n",
      " -5.65   6.57   7.19  -0.63  -0.48   3.15 energies\n",
      "cost score: 4.811521858803953\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.93  -0.67   5.52   9.71   0.13   3.36 weighted difference from target energies\n",
      " -7.20   5.33   5.48  -0.15  -0.61   2.36 energies\n",
      "cost score: 5.660526640416999\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.18  -0.26   2.83   5.13  -0.09   2.80 weighted difference from target energies\n",
      " -6.45   5.74   8.17  -2.43  -1.27   1.80 energies\n",
      "cost score: 3.7825618670290706\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.59  -0.34   5.02   9.35   0.39   2.72 weighted difference from target energies\n",
      " -5.24   5.66   5.98  -0.32   0.16   1.72 energies\n",
      "cost score: 5.201924227896158\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.08   4.38   0.97  10.70   0.02   3.21 weighted difference from target energies\n",
      " -6.77  10.38  10.03   0.35  -0.93   2.21 energies\n",
      "cost score: 4.756932001535501\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.07   4.89   0.87  11.50  -0.07   2.92 weighted difference from target energies\n",
      " -6.80  10.89  10.13   0.75  -1.20   1.92 energies\n",
      "cost score: 5.089335894502721\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.83   4.68   1.21  11.79   0.06   3.28 weighted difference from target energies\n",
      " -7.52  10.68   9.79   0.89  -0.83   2.28 energies\n",
      "cost score: 4.9768640815122165\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.27   4.15   1.25  10.79  -0.04   3.02 weighted difference from target energies\n",
      " -6.20  10.15   9.75   0.40  -1.12   2.02 energies\n",
      "cost score: 4.58245820727271\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.23   5.34   0.79  12.26   1.04   3.34 weighted difference from target energies\n",
      " -6.31  11.34  10.21   1.13   2.12   2.34 energies\n",
      "cost score: 5.527229458972926\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.56   5.49  -2.09   6.81  -0.06   2.90 weighted difference from target energies\n",
      " -5.31  11.49  13.09  -1.60  -1.18   1.90 energies\n",
      "cost score: 5.61434960821881\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.67   2.77   2.07   9.69   0.72   3.01 weighted difference from target energies\n",
      " -4.99   8.77   8.93  -0.16   1.15   2.01 energies\n",
      "cost score: 4.105863905826067\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.12   3.84   0.86   9.39   0.66   3.02 weighted difference from target energies\n",
      " -6.63   9.84  10.14  -0.31   0.99   2.02 energies\n",
      "cost score: 4.376058001969505\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.95   4.03   1.13  10.33   0.56   2.72 weighted difference from target energies\n",
      " -7.14  10.03   9.87   0.17   0.68   1.72 energies\n",
      "cost score: 4.425049488065882\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  3.32   4.50  -0.63   7.74   1.30   3.89 weighted difference from target energies\n",
      " -3.03  10.50  11.63  -1.13   2.89   2.89 energies\n",
      "cost score: 5.1414331159175966\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.00   3.76   1.25  10.02   0.55   2.74 weighted difference from target energies\n",
      " -6.99   9.76   9.75   0.01   0.65   1.74 energies\n",
      "cost score: 4.262435844673778\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.73   4.33   1.29  11.23   0.56   2.75 weighted difference from target energies\n",
      " -7.82  10.33   9.71   0.62   0.67   1.75 energies\n",
      "cost score: 4.630903809512182\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.34   4.35   1.63  11.94   0.38   2.10 weighted difference from target energies\n",
      " -8.99  10.35   9.37   0.97   0.15   1.10 energies\n",
      "cost score: 4.5614621280255285\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.73   4.01   1.79  11.58   0.32   3.33 weighted difference from target energies\n",
      " -7.81  10.01   9.21   0.79  -0.03   2.33 energies\n",
      "cost score: 4.563066549433656\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.82   3.37   2.13  11.02   1.17   3.97 weighted difference from target energies\n",
      " -7.54   9.37   8.87   0.51   2.52   2.97 energies\n",
      "cost score: 4.605542396396766\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.88   3.37   1.96  10.67   1.19   3.86 weighted difference from target energies\n",
      " -7.37   9.37   9.04   0.34   2.58   2.86 energies\n",
      "cost score: 4.539219212194837\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.75   3.36   2.37  11.46   1.03   3.52 weighted difference from target energies\n",
      " -7.74   9.36   8.63   0.73   2.09   2.52 energies\n",
      "cost score: 4.404293530049002\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.69   3.35   3.32  13.35   0.98   3.49 weighted difference from target energies\n",
      " -7.94   9.35   7.68   1.67   1.94   2.49 energies\n",
      "cost score: 4.575651068135388\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.06   2.88   4.52  14.80  -0.04   2.91 weighted difference from target energies\n",
      " -6.81   8.88   6.48   2.40  -1.11   1.91 energies\n",
      "cost score: 4.917816016658818\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.13   0.46   4.52   9.95  -0.04   2.91 weighted difference from target energies\n",
      " -6.61   6.46   6.48  -0.02  -1.11   1.91 energies\n",
      "cost score: 4.795041720436074\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.57   1.02   4.51  11.08  -0.04   3.00 weighted difference from target energies\n",
      " -8.30   7.02   6.49   0.54  -1.13   2.00 energies\n",
      "cost score: 4.787461069606181\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.53   0.01   4.60   9.22  -0.04   2.86 weighted difference from target energies\n",
      " -8.42   6.01   6.40  -0.39  -1.11   1.86 energies\n",
      "cost score: 4.819465087505325\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.23   1.38   2.77   8.30   0.95   2.96 weighted difference from target energies\n",
      " -9.32   7.38   8.23  -0.85   1.84   1.96 energies\n",
      "cost score: 3.8119129835713954\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.00   3.64  -0.76   5.76   1.10   3.65 weighted difference from target energies\n",
      " -6.99   9.64  11.76  -2.12   2.31   2.65 energies\n",
      "cost score: 4.470935580609154\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.91   4.19  -1.82   4.73   1.10   3.65 weighted difference from target energies\n",
      " -7.26  10.19  12.82  -2.63   2.31   2.65 energies\n",
      "cost score: 4.739949163461654\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.50   1.38   3.29   9.35   0.52   1.82 weighted difference from target energies\n",
      " -8.50   7.38   7.71  -0.33   0.57   0.82 energies\n",
      "cost score: 3.7662542718979575\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.19   2.01   0.03   4.08   0.91   3.02 weighted difference from target energies\n",
      " -6.44   8.01  10.97  -2.96   1.72   2.02 energies\n",
      "cost score: 3.6983930237661244\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.02   5.22   2.82  16.08   1.13   3.83 weighted difference from target energies\n",
      " -6.93  11.22   8.18   3.04   2.39   2.83 energies\n",
      "cost score: 5.552616406808348\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.03   7.11   0.89  16.01   1.13   3.83 weighted difference from target energies\n",
      " -6.91  13.11  10.11   3.01   2.38   2.83 energies\n",
      "cost score: 7.158515631255876\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.75   3.72   1.02   9.47   1.21   5.70 weighted difference from target energies\n",
      " -4.74   9.72   9.98  -0.26   2.62   4.70 energies\n",
      "cost score: 5.890954653786599\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.97   3.37   0.66   8.06   1.28   4.52 weighted difference from target energies\n",
      " -7.09   9.37  10.34  -0.97   2.83   3.52 energies\n",
      "cost score: 4.894754991337415\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.90   4.18  -1.32   5.73   0.68   3.71 weighted difference from target energies\n",
      " -7.29  10.18  12.32  -2.13   1.04   2.71 energies\n",
      "cost score: 4.747677852367827\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.26   4.81   2.24  14.09   0.05   3.13 weighted difference from target energies\n",
      " -9.21  10.81   8.76   2.05  -0.84   2.13 energies\n",
      "cost score: 5.0697329345023405\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.90   1.82   0.46   4.56   0.69   3.66 weighted difference from target energies\n",
      " -7.31   7.82  10.54  -2.72   1.06   2.66 energies\n",
      "cost score: 4.012107206022365\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.91   1.68   0.56   4.47   0.72   3.65 weighted difference from target energies\n",
      " -7.27   7.68  10.44  -2.76   1.15   2.65 energies\n",
      "cost score: 3.99579530252334\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.60   2.41   0.83   6.48   0.51   2.41 weighted difference from target energies\n",
      " -8.20   8.41  10.17  -1.76   0.53   1.41 energies\n",
      "cost score: 3.4393440567135087\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.67   1.86   0.85   5.42   0.36   2.66 weighted difference from target energies\n",
      " -8.00   7.86  10.15  -2.29   0.09   1.66 energies\n",
      "cost score: 3.393721714741545\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.26   1.86   0.86   5.43   0.02   1.92 weighted difference from target energies\n",
      " -9.22   7.86  10.14  -2.28  -0.95   0.92 energies\n",
      "cost score: 3.0021308045043025\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.42   3.01   0.61   7.22   0.58   2.78 weighted difference from target energies\n",
      " -5.75   9.01  10.39  -1.39   0.75   1.78 energies\n",
      "cost score: 3.9346306753365483\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.06   2.43   0.85   6.56   0.02   1.91 weighted difference from target energies\n",
      " -9.83   8.43  10.15  -1.72  -0.95   0.91 energies\n",
      "cost score: 3.1930967526264165\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.06   1.81   0.46   4.53   0.24   1.11 weighted difference from target energies\n",
      "-12.82   7.81  10.54  -2.73  -0.29   0.11 energies\n",
      "cost score: 2.567232043141774\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.02   2.61   0.21   5.63   0.13   0.90 weighted difference from target energies\n",
      "-12.93   8.61  10.79  -2.18  -0.62  -0.10 energies\n",
      "cost score: 2.9646350991066805\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.32   3.55   0.23   7.56   0.13   0.90 weighted difference from target energies\n",
      "-13.95   9.55  10.77  -1.22  -0.62  -0.10 energies\n",
      "cost score: 3.698287149793599\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.35   3.92   0.16   8.14   0.23   1.30 weighted difference from target energies\n",
      "-14.06   9.92  10.84  -0.93  -0.32   0.30 energies\n",
      "cost score: 4.042081478963883\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.89   4.35   0.32   9.33   0.22   1.30 weighted difference from target energies\n",
      "-15.68  10.35  10.68  -0.34  -0.35   0.30 energies\n",
      "cost score: 4.42880896428977\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.05   4.04   0.97  10.03   0.21   1.03 weighted difference from target energies\n",
      "-16.16  10.04  10.03   0.01  -0.38   0.03 energies\n",
      "cost score: 4.158393228535344\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.98   4.04   0.69   9.46   0.17   0.50 weighted difference from target energies\n",
      "-15.93  10.04  10.31  -0.27  -0.50  -0.50 energies\n",
      "cost score: 4.127985618185056\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.02   2.32   1.88   8.40   0.15   0.46 weighted difference from target energies\n",
      "-16.06   8.32   9.12  -0.80  -0.54  -0.54 energies\n",
      "cost score: 2.986625665818761\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.05   1.67   2.15   7.64   0.26   1.87 weighted difference from target energies\n",
      " -9.84   7.67   8.85  -1.18  -0.22   0.87 energies\n",
      "cost score: 3.199838867727474\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.27   1.68   3.31   9.99  -0.15   0.62 weighted difference from target energies\n",
      " -9.20   7.68   7.69  -0.01  -1.46  -0.38 energies\n",
      "cost score: 3.6672103989084643\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.27   4.16   0.84  10.00  -0.15   0.62 weighted difference from target energies\n",
      " -9.20  10.16  10.16  -0.00  -1.46  -0.38 energies\n",
      "cost score: 4.285119866469384\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.26   1.68   3.32  10.00  -0.16   0.61 weighted difference from target energies\n",
      " -9.21   7.68   7.68  -0.00  -1.47  -0.39 energies\n",
      "cost score: 3.6693172693769744\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.26   1.68   3.32  10.00  -0.16   0.61 weighted difference from target energies\n",
      " -9.21   7.68   7.68  -0.00  -1.47  -0.39 energies\n",
      "cost score: 3.6693045809895493\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.99   1.68   2.31   7.98   0.20   1.68 weighted difference from target energies\n",
      "-15.97   7.68   8.69  -1.01  -0.39   0.68 energies\n",
      "cost score: 3.108649132855542\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.94   1.68   2.52   8.42   0.22   0.66 weighted difference from target energies\n",
      "-18.83   7.68   8.48  -0.79  -0.34  -0.34 energies\n",
      "cost score: 3.053941645475791\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -2.21   4.03   0.97  10.00  -0.02  -0.06 weighted difference from target energies\n",
      "-19.62  10.03  10.03   0.00  -1.06  -1.06 energies\n",
      "cost score: 4.107398467630037\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -2.11   3.28   2.74  12.05   0.08   0.24 weighted difference from target energies\n",
      "-19.32   9.28   8.26   1.02  -0.76  -0.76 energies\n",
      "cost score: 3.798813591142471\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -2.12   3.28   2.96  12.49   0.24   0.72 weighted difference from target energies\n",
      "-19.36   9.28   8.04   1.25  -0.28  -0.28 energies\n",
      "cost score: 3.901108301686204\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -2.25   5.28   1.34  13.22   0.11   0.33 weighted difference from target energies\n",
      "-19.76  11.28   9.66   1.61  -0.67  -0.67 energies\n",
      "cost score: 5.308761966029921\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.61   6.99   2.14  18.25   0.17   0.50 weighted difference from target energies\n",
      "-14.83  12.99   8.86   4.12  -0.50  -0.50 energies\n",
      "cost score: 6.995995138952948\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -2.12   3.28   2.96  12.48   0.24   0.73 weighted difference from target energies\n",
      "-19.36   9.28   8.04   1.24  -0.27  -0.27 energies\n",
      "cost score: 3.900410272951895\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.03   1.96   3.34  10.59   0.72   2.17 weighted difference from target energies\n",
      "-16.09   7.96   7.66   0.29   1.17   1.17 energies\n",
      "cost score: 3.837044111079573\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.03   1.95   3.33  10.57   0.72   2.17 weighted difference from target energies\n",
      "-16.08   7.95   7.67   0.29   1.17   1.17 energies\n",
      "cost score: 3.8349760423347594\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.03   1.96   3.33  10.59   0.72   2.17 weighted difference from target energies\n",
      "-16.09   7.96   7.67   0.30   1.17   1.17 energies\n",
      "cost score: 3.8364830456966543\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.97   1.63   3.33   9.92   0.72   2.17 weighted difference from target energies\n",
      "-15.92   7.63   7.67  -0.04   1.17   1.17 energies\n",
      "cost score: 3.789571822057407\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.89   1.42   3.34   9.52   0.72   2.17 weighted difference from target energies\n",
      "-15.66   7.42   7.66  -0.24   1.17   1.17 energies\n",
      "cost score: 3.7719381433160577\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.30   2.77   3.31  12.14   0.72   2.16 weighted difference from target energies\n",
      "-16.89   8.77   7.69   1.07   1.16   1.16 energies\n",
      "cost score: 3.9919327044288138\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.95   2.77   4.64  14.82   0.27   0.80 weighted difference from target energies\n",
      "-18.86   8.77   6.36   2.41  -0.20  -0.20 energies\n",
      "cost score: 4.816889418060084\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.39   0.08   3.30   6.76   0.72   2.16 weighted difference from target energies\n",
      "-14.18   6.08   7.70  -1.62   1.16   1.16 energies\n",
      "cost score: 3.6797644675372627\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.37  -0.02   3.34   6.64   0.72   2.17 weighted difference from target energies\n",
      "-14.12   5.98   7.66  -1.68   1.17   1.17 energies\n",
      "cost score: 3.7053261886271134\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.37  -0.02   3.34   6.64   0.72   2.17 weighted difference from target energies\n",
      "-14.11   5.98   7.66  -1.68   1.17   1.17 energies\n",
      "cost score: 3.7055352640732355\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.09   0.38   3.03   6.81   0.84   3.12 weighted difference from target energies\n",
      "-12.72   6.38   7.97  -1.60   1.52   2.12 energies\n",
      "cost score: 3.8741073267752917\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.41   0.58   3.96   9.07   0.14   1.75 weighted difference from target energies\n",
      "-14.23   6.58   7.04  -0.46  -0.59   0.75 energies\n",
      "cost score: 4.120962334171317\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.40   0.59   3.91   8.99   0.15   1.80 weighted difference from target energies\n",
      "-14.19   6.59   7.09  -0.50  -0.54   0.80 energies\n",
      "cost score: 4.08625403419592\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.40   0.58   3.93   9.04   0.14   1.77 weighted difference from target energies\n",
      "-14.21   6.58   7.07  -0.48  -0.57   0.77 energies\n",
      "cost score: 4.1043512112461675\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.62   1.13   2.82   7.91   0.62   1.87 weighted difference from target energies\n",
      "-14.87   7.13   8.18  -1.05   0.87   0.87 energies\n",
      "cost score: 3.3612503638779616\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.63   1.13   2.85   7.96   0.65   1.94 weighted difference from target energies\n",
      "-14.89   7.13   8.15  -1.02   0.94   0.94 energies\n",
      "cost score: 3.396510777983985\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.58   1.11   3.23   8.67   0.63   1.89 weighted difference from target energies\n",
      "-14.73   7.11   7.77  -0.67   0.89   0.89 energies\n",
      "cost score: 3.6198293422730434\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.58   1.11   3.23   8.67   0.63   1.89 weighted difference from target energies\n",
      "-14.73   7.11   7.77  -0.67   0.89   0.89 energies\n",
      "cost score: 3.6198631954111344\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.59   1.18   3.20   8.76   0.63   1.89 weighted difference from target energies\n",
      "-14.77   7.18   7.80  -0.62   0.89   0.89 energies\n",
      "cost score: 3.6047546226825364\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.70   1.23   3.77  10.00   0.42   1.25 weighted difference from target energies\n",
      "-15.10   7.23   7.23   0.00   0.25   0.25 energies\n",
      "cost score: 3.9551856849956444\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.90   1.70   2.94   9.27   0.29   0.87 weighted difference from target energies\n",
      "-15.69   7.70   8.06  -0.36  -0.13  -0.13 energies\n",
      "cost score: 3.34853475400804\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.29   0.32   4.36   9.34   0.21   0.63 weighted difference from target energies\n",
      "-16.86   6.32   6.64  -0.33  -0.37  -0.37 energies\n",
      "cost score: 4.4144154951515775\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.90   1.70   2.94   9.27   0.29   0.87 weighted difference from target energies\n",
      "-15.69   7.70   8.06  -0.36  -0.13  -0.13 energies\n",
      "cost score: 3.3485625586359107\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.90   1.70   2.94   9.27   0.29   0.87 weighted difference from target energies\n",
      "-15.69   7.70   8.06  -0.36  -0.13  -0.13 energies\n",
      "cost score: 3.3485625586359107\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.90   1.70   2.94   9.27   0.29   0.87 weighted difference from target energies\n",
      "-15.69   7.70   8.06  -0.36  -0.13  -0.13 energies\n",
      "cost score: 3.3485625586359107\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.93   3.56   1.19   9.50   0.27   0.82 weighted difference from target energies\n",
      "-15.80   9.56   9.81  -0.25  -0.18  -0.18 energies\n",
      "cost score: 3.7444758448427504\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.38   3.56   1.21   9.53   0.18   0.55 weighted difference from target energies\n",
      "-17.14   9.56   9.79  -0.24  -0.45  -0.45 energies\n",
      "cost score: 3.72666711439614\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.38   3.56   1.21   9.52   0.18   0.54 weighted difference from target energies\n",
      "-17.14   9.56   9.79  -0.24  -0.46  -0.46 energies\n",
      "cost score: 3.7260002041545897\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.38   3.36   1.21   9.13   0.18   0.55 weighted difference from target energies\n",
      "-17.14   9.36   9.79  -0.43  -0.45  -0.45 energies\n",
      "cost score: 3.563092261354725\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.48   3.36   1.34   9.40   0.22   0.65 weighted difference from target energies\n",
      "-17.45   9.36   9.66  -0.30  -0.35  -0.35 energies\n",
      "cost score: 3.5820769564543333\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.83   0.17   1.84   4.03  -0.07  -0.20 weighted difference from target energies\n",
      "-15.50   6.17   9.16  -2.99  -1.20  -1.20 energies\n",
      "cost score: 2.268796945574388\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.38  -1.18   1.84   1.31  -0.07  -0.20 weighted difference from target energies\n",
      "-14.13   4.82   9.16  -4.34  -1.20  -1.20 energies\n",
      "cost score: 2.201205141037327\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.52  -0.71  -1.14  -3.71  -0.07  -0.20 weighted difference from target energies\n",
      "-11.44   5.29  12.14  -6.86  -1.20  -1.20 energies\n",
      "cost score: 1.4458152091350438\n",
      "AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU AUGUUAGACUACUGUUUGGCGGCCGUAUUUAAAGAUUUGUUACGCUGGGGAAUCGCGCUCGUUCGCAGCCAGCCGUAGAAAAGGCGAGUUCCGCUCCCGUAGUUCUACGCGUUCCGGUUAGGUAAGGGCGAGCGUGAUAGGAGCCCCGGUAUGAGUAAAGGAGAAGAACUUUUCACU 1.4458152091350438\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.52  -0.71  -1.14  -3.71  -0.07  -0.20 weighted difference from target energies\n",
      "-11.44   5.29  12.14  -6.86  -1.20  -1.20 energies\n",
      "cost score: 1.4458152091350438\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.52  -0.71  -1.14  -3.71  -0.07  -0.20 weighted difference from target energies\n",
      "-11.44   5.29  12.14  -6.86  -1.20  -1.20 energies\n",
      "cost score: 1.445815936118425\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.30  -0.71  -2.70  -6.81  -0.12  -0.37 weighted difference from target energies\n",
      " -9.10   5.29  13.70  -8.41  -1.37  -1.37 energies\n",
      "cost score: 1.7582410269121933\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.02   7.13  -1.25  11.76  -0.03  -0.08 weighted difference from target energies\n",
      " -9.93  13.13  12.25   0.88  -1.08  -1.08 energies\n",
      "cost score: 7.134695077455681\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.52  -0.71  -1.14  -3.71  -0.07  -0.20 weighted difference from target energies\n",
      "-11.44   5.29  12.14  -6.86  -1.20  -1.20 energies\n",
      "cost score: 1.4458358075977693\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.34  -0.34  -0.22  -1.11  -0.06  -0.18 weighted difference from target energies\n",
      "-11.97   5.66  11.22  -5.55  -1.18  -1.18 energies\n",
      "cost score: 1.5487071020532313\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.24   1.46  -0.48   1.97  -0.04  -0.13 weighted difference from target energies\n",
      "-13.72   7.46  11.48  -4.02  -1.13  -1.13 energies\n",
      "cost score: 2.0237947162015133\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.43  -0.57   0.27  -0.61  -0.06  -0.17 weighted difference from target energies\n",
      "-11.72   5.43  10.73  -5.31  -1.17  -1.17 energies\n",
      "cost score: 1.646794744118024\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.46  -0.69   0.23  -0.92  -0.06  -0.17 weighted difference from target energies\n",
      "-11.61   5.31  10.77  -5.46  -1.17  -1.17 energies\n",
      "cost score: 1.636619101223022\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.06   1.00   1.57   5.15   0.10   0.30 weighted difference from target energies\n",
      "-12.81   7.00   9.43  -2.43  -0.70  -0.70 energies\n",
      "cost score: 2.403334766501459\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.64  -1.05   0.02  -2.08  -0.06  -0.18 weighted difference from target energies\n",
      "-11.07   4.95  10.98  -6.04  -1.18  -1.18 energies\n",
      "cost score: 1.618350552308892\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.37   3.35  -0.13   6.44   0.28   0.84 weighted difference from target energies\n",
      "-14.11   9.35  11.13  -1.78  -0.16  -0.16 energies\n",
      "cost score: 3.520090967724388\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.13   1.54  -0.18   2.73   0.02   0.07 weighted difference from target energies\n",
      "-13.38   7.54  11.18  -3.63  -0.93  -0.93 energies\n",
      "cost score: 2.1390994260308767\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.64  -1.06   0.02  -2.08  -0.06  -0.18 weighted difference from target energies\n",
      "-11.07   4.94  10.98  -6.04  -1.18  -1.18 energies\n",
      "cost score: 1.618165914041144\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.69  -1.33  -0.03  -2.71  -0.05  -0.14 weighted difference from target energies\n",
      "-10.93   4.67  11.03  -6.36  -1.14  -1.14 energies\n",
      "cost score: 1.6204679435661962\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.28   0.79  -2.21  -2.84   0.39   1.17 weighted difference from target energies\n",
      " -9.17   6.79  13.21  -6.42   0.17   0.17 energies\n",
      "cost score: 2.3606010398135067\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.40  -0.46   0.01  -0.91  -0.05  -0.14 weighted difference from target energies\n",
      "-11.80   5.54  10.99  -5.45  -1.14  -1.14 energies\n",
      "cost score: 1.599893085790753\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.41  -0.45   0.50   0.11  -0.03  -0.10 weighted difference from target energies\n",
      "-11.77   5.55  10.50  -4.95  -1.10  -1.10 energies\n",
      "cost score: 1.735255022887691\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.16   1.58  -0.43   2.29   0.09   0.26 weighted difference from target energies\n",
      "-13.48   7.58  11.43  -3.86  -0.74  -0.74 energies\n",
      "cost score: 2.1664169677131433\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.53  -0.37   0.10  -0.55   0.09   0.26 weighted difference from target energies\n",
      "-11.42   5.63  10.90  -5.28  -0.74  -0.74 energies\n",
      "cost score: 1.7698077870761737\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.77  -1.10  -0.25  -2.71   0.08   0.24 weighted difference from target energies\n",
      "-10.70   4.90  11.25  -6.36  -0.76  -0.76 energies\n",
      "cost score: 1.7253834859929897\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.52   0.07   1.41   2.97   0.20   0.59 weighted difference from target energies\n",
      "-11.43   6.07   9.59  -3.51  -0.41  -0.41 energies\n",
      "cost score: 2.292298024341857\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.78   0.46   1.76   4.45   0.37   1.11 weighted difference from target energies\n",
      "-10.65   6.46   9.24  -2.78   0.11   0.11 energies\n",
      "cost score: 2.6449204433219426\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.36   0.10  -0.45  -0.69   0.08   0.24 weighted difference from target energies\n",
      "-11.92   6.10  11.45  -5.35  -0.76  -0.76 energies\n",
      "cost score: 1.7107092430292958\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.25   0.44  -0.46  -0.03   0.08   0.24 weighted difference from target energies\n",
      "-12.25   6.44  11.46  -5.02  -0.76  -0.76 energies\n",
      "cost score: 1.7617613883306902\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.36   0.10  -0.45  -0.69   0.08   0.24 weighted difference from target energies\n",
      "-11.92   6.10  11.45  -5.35  -0.76  -0.76 energies\n",
      "cost score: 1.7107092430292958\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.57  -0.52  -0.45  -1.94   0.08   0.24 weighted difference from target energies\n",
      "-11.30   5.48  11.45  -5.97  -0.76  -0.76 energies\n",
      "cost score: 1.676689737221114\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.21   1.83  -0.45   2.75   0.08   0.24 weighted difference from target energies\n",
      "-13.64   7.83  11.45  -3.63  -0.76  -0.76 energies\n",
      "cost score: 2.3042345978930903\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.58  -0.39   0.97   1.16   0.13   0.38 weighted difference from target energies\n",
      "-11.26   5.61  10.03  -4.42  -0.62  -0.62 energies\n",
      "cost score: 2.041668047696753\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.06  -0.39   1.85   2.92   0.40   1.19 weighted difference from target energies\n",
      "-13.18   5.61   9.15  -3.54   0.19   0.19 energies\n",
      "cost score: 2.5476622234405686\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.18  -0.54   2.34   3.59   0.51   1.54 weighted difference from target energies\n",
      "-13.54   5.46   8.66  -3.21   0.54   0.54 energies\n",
      "cost score: 2.896154025478827\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.24   1.18   1.81   5.97   0.41   1.24 weighted difference from target energies\n",
      "-13.73   7.18   9.19  -2.01   0.24   0.24 energies\n",
      "cost score: 2.7144423672643603\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.38   1.07   2.74   7.62   0.09   0.28 weighted difference from target energies\n",
      "-17.14   7.07   8.26  -1.19  -0.72  -0.72 energies\n",
      "cost score: 3.0512179930148613\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.54   1.63   2.07   7.39   0.33   0.98 weighted difference from target energies\n",
      "-17.62   7.63   8.93  -1.31  -0.02  -0.02 energies\n",
      "cost score: 2.84799124732319\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.35   1.01   2.08   6.16   0.32   0.97 weighted difference from target energies\n",
      "-17.05   7.01   8.92  -1.92  -0.03  -0.03 energies\n",
      "cost score: 2.707434356750332\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.38  -1.02   2.83   3.61   0.17   0.52 weighted difference from target energies\n",
      "-17.14   4.98   8.17  -3.19  -0.48  -0.48 energies\n",
      "cost score: 3.014093531693677\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -2.10  -0.56   5.53   9.94   0.60   1.80 weighted difference from target energies\n",
      "-19.31   5.44   5.47  -0.03   0.80   0.80 energies\n",
      "cost score: 5.566111019959254\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.51  -1.25   3.38   4.26   0.24   0.73 weighted difference from target energies\n",
      "-17.52   4.75   7.62  -2.87  -0.27  -0.27 energies\n",
      "cost score: 3.499941335787847\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.59   0.68   4.01   9.37   0.27   0.81 weighted difference from target energies\n",
      "-17.78   6.68   6.99  -0.32  -0.19  -0.19 energies\n",
      "cost score: 4.104990617983983\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.65   3.36   2.15  11.02   0.51   1.54 weighted difference from target energies\n",
      "-17.95   9.36   8.85   0.51   0.54   0.54 energies\n",
      "cost score: 3.782706848113544\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.26   1.50   4.78  12.56   0.23   0.68 weighted difference from target energies\n",
      "-12.23   7.50   6.22   1.28  -0.32  -0.32 energies\n",
      "cost score: 4.852800737657605\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.09   2.79   4.65  14.87   0.20   0.60 weighted difference from target energies\n",
      "-13.26   8.79   6.35   2.43  -0.40  -0.40 energies\n",
      "cost score: 4.82483685722626\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.00   2.06   4.69  13.50   0.17   0.51 weighted difference from target energies\n",
      "-13.01   8.06   6.31   1.75  -0.49  -0.49 energies\n",
      "cost score: 4.789940559776758\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.90  -0.63   4.29   7.32   0.11   0.83 weighted difference from target energies\n",
      "-10.30   5.37   6.71  -1.34  -0.67  -0.17 energies\n",
      "cost score: 4.376904933625323\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.15   6.87   0.25  14.24   0.13   0.39 weighted difference from target energies\n",
      " -9.54  12.87  10.75   2.12  -0.61  -0.61 energies\n",
      "cost score: 6.8742370074945525\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.17  -0.95   4.29   6.68   0.11   0.94 weighted difference from target energies\n",
      " -9.49   5.05   6.71  -1.66  -0.67  -0.06 energies\n",
      "cost score: 4.385462636340144\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.75  -0.91   0.55  -0.73  -0.09   0.00 weighted difference from target energies\n",
      "-10.75   5.09  10.45  -5.36  -1.27  -1.00 energies\n",
      "cost score: 1.8182928014573045\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.94  -1.19   0.31  -1.76  -0.02   0.22 weighted difference from target energies\n",
      "-10.19   4.81  10.69  -5.88  -1.05  -0.78 energies\n",
      "cost score: 1.863793620906373\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.97  -1.28   0.31  -1.94  -0.02   0.22 weighted difference from target energies\n",
      "-10.10   4.72  10.69  -5.97  -1.05  -0.78 energies\n",
      "cost score: 1.8718479208760261\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.93  -1.17   0.31  -1.73  -0.02   0.22 weighted difference from target energies\n",
      "-10.21   4.83  10.69  -5.86  -1.05  -0.78 energies\n",
      "cost score: 1.8619866040744377\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.07  -1.25   1.03  -0.44   0.20   0.59 weighted difference from target energies\n",
      "-13.21   4.75   9.97  -5.22  -0.41  -0.41 energies\n",
      "cost score: 1.950543059501562\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.09  -1.09   0.81  -0.57   0.27   0.80 weighted difference from target energies\n",
      "-13.26   4.91  10.19  -5.28  -0.20  -0.20 energies\n",
      "cost score: 1.9492100979232265\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.98  -1.22  -1.57  -5.59   0.74   5.01 weighted difference from target energies\n",
      " -7.06   4.78  12.57  -7.79   1.22   4.01 energies\n",
      "cost score: 5.073583348548503\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.15  -1.27   0.61  -1.34   0.24   0.71 weighted difference from target energies\n",
      "-12.56   4.73  10.39  -5.67  -0.29  -0.29 energies\n",
      "cost score: 1.882768541540103\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.53  -1.56   4.59   6.06   0.25   0.74 weighted difference from target energies\n",
      "-17.58   4.44   6.41  -1.97  -0.26  -0.26 energies\n",
      "cost score: 4.63181963653061\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.46   0.38   0.78   2.32   0.26   0.77 weighted difference from target energies\n",
      "-14.39   6.38  10.22  -3.84  -0.23  -0.23 energies\n",
      "cost score: 2.045116772461446\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.32   0.38   0.81   2.38   0.40   1.43 weighted difference from target energies\n",
      "-12.05   6.38  10.19  -3.81   0.19   0.43 energies\n",
      "cost score: 2.3750616208638005\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.37   0.11   0.78   1.78   0.26   0.77 weighted difference from target energies\n",
      "-14.12   6.11  10.22  -4.11  -0.23  -0.23 energies\n",
      "cost score: 2.0062832459390822\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.37   0.11   0.78   1.77   0.26   0.77 weighted difference from target energies\n",
      "-14.12   6.11  10.22  -4.11  -0.23  -0.23 energies\n",
      "cost score: 2.006154054132292\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.38   0.12   0.78   1.80   0.26   0.77 weighted difference from target energies\n",
      "-14.13   6.12  10.22  -4.10  -0.23  -0.23 energies\n",
      "cost score: 2.0082021945753725\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.29  -0.12   0.78   1.32   0.26   0.77 weighted difference from target energies\n",
      "-13.88   5.88  10.22  -4.34  -0.23  -0.23 energies\n",
      "cost score: 1.9822876059002401\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.29  -0.12   0.78   1.32   0.26   0.77 weighted difference from target energies\n",
      "-13.88   5.88  10.22  -4.34  -0.23  -0.23 energies\n",
      "cost score: 1.9822890092389476\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.01  -0.12   1.06   1.88   0.29   0.86 weighted difference from target energies\n",
      "-12.96   5.88   9.94  -4.06  -0.14  -0.14 energies\n",
      "cost score: 2.137247652650452\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.29  -0.12   0.78   1.32   0.26   0.77 weighted difference from target energies\n",
      "-13.88   5.88  10.22  -4.34  -0.23  -0.23 energies\n",
      "cost score: 1.9822843314980525\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.07  -0.12   0.75   1.27   0.28   0.83 weighted difference from target energies\n",
      "-13.20   5.88  10.25  -4.37  -0.17  -0.17 energies\n",
      "cost score: 2.0218872476733383\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.07  -0.12   0.75   1.27   0.28   0.83 weighted difference from target energies\n",
      "-13.20   5.88  10.25  -4.37  -0.17  -0.17 energies\n",
      "cost score: 2.021896746824056\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.21  -0.13   0.78   1.30   0.31   0.93 weighted difference from target energies\n",
      "-13.62   5.87  10.22  -4.35  -0.07  -0.07 energies\n",
      "cost score: 2.0514184918906357\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.16  -0.05   2.80   5.50   0.51   1.53 weighted difference from target energies\n",
      "-12.53   5.95   8.20  -2.25   0.53   0.53 energies\n",
      "cost score: 3.2137587198415103\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.21  -0.12   0.79   1.33   0.31   0.93 weighted difference from target energies\n",
      "-13.62   5.88  10.21  -4.34  -0.07  -0.07 energies\n",
      "cost score: 2.0533833430813697\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.50   0.19  -0.39  -0.40   0.34   1.03 weighted difference from target energies\n",
      " -8.49   6.19  11.39  -5.20   0.03   0.03 energies\n",
      "cost score: 2.360339731405623\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.85   1.59   1.00   5.18   0.35   1.05 weighted difference from target energies\n",
      "-10.44   7.59  10.00  -2.41   0.05   0.05 energies\n",
      "cost score: 2.6568494869383428\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.37   0.59  -0.34   0.50   0.34   1.03 weighted difference from target energies\n",
      " -8.90   6.59  11.34  -4.75   0.03   0.03 energies\n",
      "cost score: 2.3657306264462843\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.68   2.58   2.30   9.77  -0.06  -0.17 weighted difference from target energies\n",
      "-15.03   8.58   8.70  -0.12  -1.17  -1.17 energies\n",
      "cost score: 3.238624912036003\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.40   0.48  -0.35   0.25   0.34   1.03 weighted difference from target energies\n",
      " -8.79   6.48  11.35  -4.87   0.03   0.03 energies\n",
      "cost score: 2.3607322377843922\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.46   0.33  -0.38  -0.10   0.34   1.03 weighted difference from target energies\n",
      " -8.63   6.33  11.38  -5.05   0.03   0.03 energies\n",
      "cost score: 2.3587794054204987\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.40   0.33  -0.27   0.11   0.28   0.84 weighted difference from target energies\n",
      " -8.81   6.33  11.27  -4.94  -0.16  -0.16 energies\n",
      "cost score: 2.2857135222168914\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.63   1.97   0.90   5.74   0.41   1.22 weighted difference from target energies\n",
      "-11.10   7.97  10.10  -2.13   0.22   0.22 energies\n",
      "cost score: 2.796685746346994\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.77   2.07   1.85   7.84   0.15   0.45 weighted difference from target energies\n",
      "-10.68   8.07   9.15  -1.08  -0.55  -0.55 energies\n",
      "cost score: 2.954290761843981\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.72   2.08   1.33   6.82   0.27   0.81 weighted difference from target energies\n",
      "-10.83   8.08   9.67  -1.59  -0.19  -0.19 energies\n",
      "cost score: 2.8575744275352575\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.23   0.81  -0.13   1.36   0.28   0.83 weighted difference from target energies\n",
      " -9.30   6.81  11.13  -4.32  -0.17  -0.17 energies\n",
      "cost score: 2.3202421069172723\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.37   2.58   2.27   9.69   0.22   0.66 weighted difference from target energies\n",
      "-17.11   8.58   8.73  -0.15  -0.34  -0.34 energies\n",
      "cost score: 3.2685009859415555\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.01   1.73   0.81   5.08   0.48   1.45 weighted difference from target energies\n",
      " -9.98   7.73  10.19  -2.46   0.45   0.45 energies\n",
      "cost score: 2.8028752842479987\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.96   1.53   0.02   3.09   0.37   1.11 weighted difference from target energies\n",
      "-10.13   7.53  10.98  -3.46   0.11   0.11 energies\n",
      "cost score: 2.5416882816740474\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.67  10.75  -2.79  15.93   0.14   0.41 weighted difference from target energies\n",
      "-10.98  16.75  13.79   2.97  -0.59  -0.59 energies\n",
      "cost score: 10.755089388268662\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.61   2.27   0.57   5.69   0.49   1.48 weighted difference from target energies\n",
      "-11.17   8.27  10.43  -2.16   0.48   0.48 energies\n",
      "cost score: 2.961075550244455\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.26   0.71   0.22   1.85   0.31   0.92 weighted difference from target energies\n",
      " -9.22   6.71  10.78  -4.07  -0.08  -0.08 energies\n",
      "cost score: 2.3671161522109867\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.62   2.44   0.99   6.85   0.53   1.60 weighted difference from target energies\n",
      "-11.14   8.44  10.01  -1.58   0.60   0.60 energies\n",
      "cost score: 3.1192096975655583\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.25   2.49   0.53   6.04   0.55   1.65 weighted difference from target energies\n",
      "-12.26   8.49  10.47  -1.98   0.65   0.65 energies\n",
      "cost score: 3.08914576426682\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.20   2.49   0.17   5.32   0.76   2.27 weighted difference from target energies\n",
      "-12.40   8.49  10.83  -2.34   1.27   1.27 energies\n",
      "cost score: 3.2679659388403706\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.34   2.76   1.44   8.40   0.95   2.84 weighted difference from target energies\n",
      "-11.97   8.76   9.56  -0.80   1.84   1.84 energies\n",
      "cost score: 3.7175409083944144\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.11   2.50   0.69   6.38   0.75   2.24 weighted difference from target energies\n",
      "-13.33   8.50  10.31  -1.81   1.24   1.24 energies\n",
      "cost score: 3.280556745555177\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.52   2.50   2.19   9.38   0.56   1.96 weighted difference from target energies\n",
      "-14.57   8.50   8.81  -0.31   0.67   0.96 energies\n",
      "cost score: 3.4200382207730873\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.32   2.58   2.69  10.54   0.16   1.99 weighted difference from target energies\n",
      "-13.97   8.58   8.31   0.27  -0.51   0.99 energies\n",
      "cost score: 3.6153499058469984\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.54   2.59   2.11   9.41   0.38   1.43 weighted difference from target energies\n",
      "-14.63   8.59   8.89  -0.29   0.14   0.43 energies\n",
      "cost score: 3.327338115800905\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.41   2.79   2.01   9.60   0.43   1.58 weighted difference from target energies\n",
      "-11.78   8.79   8.99  -0.20   0.30   0.58 energies\n",
      "cost score: 3.454570721835757\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.74   3.98   3.10  14.16   0.56   1.68 weighted difference from target energies\n",
      "-15.21   9.98   7.90   2.08   0.68   0.68 energies\n",
      "cost score: 4.422826541133942\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.56   2.74   2.41  10.29   0.41   1.51 weighted difference from target energies\n",
      "-11.32   8.74   8.59   0.15   0.24   0.51 energies\n",
      "cost score: 3.537279970688069\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.44   4.11   1.45  11.13   0.34   1.33 weighted difference from target energies\n",
      "-11.69  10.11   9.55   0.57   0.03   0.33 energies\n",
      "cost score: 4.278677408433292\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.44   2.69   2.08   9.54   0.59   2.01 weighted difference from target energies\n",
      "-11.69   8.69   8.92  -0.23   0.77   1.01 energies\n",
      "cost score: 3.5121862212034887\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.19   2.82   3.05  11.74   0.57   1.99 weighted difference from target energies\n",
      " -9.43   8.82   7.95   0.87   0.72   0.99 energies\n",
      "cost score: 3.9178554546373965\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.90   1.83   4.08  11.81   0.57   1.93 weighted difference from target energies\n",
      "-10.31   7.83   6.92   0.91   0.72   0.93 energies\n",
      "cost score: 4.337522843264735\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.46   1.52   3.89  10.82  -0.65   1.53 weighted difference from target energies\n",
      "-11.61   7.52   7.11   0.41  -2.94   0.53 energies\n",
      "cost score: 4.096730950040017\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.27   1.75   3.93  11.36  -0.69   1.38 weighted difference from target energies\n",
      " -9.20   7.75   7.07   0.68  -3.08   0.38 energies\n",
      "cost score: 4.171346684854682\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.74   2.00   3.93  11.86  -0.69   1.38 weighted difference from target energies\n",
      "-10.78   8.00   7.07   0.93  -3.08   0.38 energies\n",
      "cost score: 4.17340873046105\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.74   2.00   3.93  11.86  -0.69   1.38 weighted difference from target energies\n",
      "-10.78   8.00   7.07   0.93  -3.08   0.38 energies\n",
      "cost score: 4.173414721906867\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.05   1.14   3.98  10.22  -0.66   1.49 weighted difference from target energies\n",
      "-12.84   7.14   7.02   0.11  -2.98   0.49 energies\n",
      "cost score: 4.133474477783498\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.50   1.14   3.99  10.25  -0.66   1.49 weighted difference from target energies\n",
      "-11.49   7.14   7.01   0.13  -2.97   0.49 energies\n",
      "cost score: 4.156107256004688\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.66   1.13   3.99  10.25  -0.66   1.49 weighted difference from target energies\n",
      "-11.02   7.13   7.01   0.13  -2.97   0.49 energies\n",
      "cost score: 4.162233924869262\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.06   2.66   3.58  12.48  -0.72   1.34 weighted difference from target energies\n",
      "-13.19   8.66   7.42   1.24  -3.16   0.34 energies\n",
      "cost score: 4.0147327578472725\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.43   5.14   2.98  16.24   0.42   1.25 weighted difference from target energies\n",
      "-17.28  11.14   8.02   3.12   0.25   0.25 energies\n",
      "cost score: 5.272774955230235\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.82   5.14   1.21  12.69   0.19   0.62 weighted difference from target energies\n",
      "-15.45  11.14   9.79   1.35  -0.43  -0.38 energies\n",
      "cost score: 5.175087554895416\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.55   6.40   1.22  15.24   0.19   0.62 weighted difference from target energies\n",
      "-14.66  12.40   9.78   2.62  -0.43  -0.38 energies\n",
      "cost score: 6.414039083685471\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.58   5.34   2.36  15.40   0.26   1.43 weighted difference from target energies\n",
      "-14.74  11.34   8.64   2.70  -0.22   0.43 energies\n",
      "cost score: 5.416159064350182\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.56   5.34   1.95  14.58   0.26   1.49 weighted difference from target energies\n",
      "-14.68  11.34   9.05   2.29  -0.23   0.49 energies\n",
      "cost score: 5.401494423901278\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.05   5.34   1.67  14.01   0.85   2.54 weighted difference from target energies\n",
      "-12.85  11.34   9.33   2.01   1.54   1.54 energies\n",
      "cost score: 5.4369526087421285\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.05   5.34   1.67  14.01   0.85   2.54 weighted difference from target energies\n",
      "-12.85  11.34   9.33   2.01   1.54   1.54 energies\n",
      "cost score: 5.436949060757546\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.30   6.45   1.67  16.24   0.85   2.54 weighted difference from target energies\n",
      "-12.09  12.45   9.33   3.12   1.54   1.54 energies\n",
      "cost score: 6.487915383731505\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.05   5.34   1.67  14.01   0.85   2.54 weighted difference from target energies\n",
      "-12.85  11.34   9.33   2.00   1.54   1.54 energies\n",
      "cost score: 5.4358283115688755\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.07   5.16   1.52  13.37   0.17   0.52 weighted difference from target energies\n",
      "-16.22  11.16   9.48   1.68  -0.48  -0.48 energies\n",
      "cost score: 5.205483180630365\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -1.33   7.63   0.89  17.05   0.50   1.50 weighted difference from target energies\n",
      "-16.98  13.63  10.11   3.52   0.50   0.50 energies\n",
      "cost score: 7.636399605766798\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.72   5.38   1.37  13.50   0.49   1.46 weighted difference from target energies\n",
      "-15.16  11.38   9.63   1.75   0.46   0.46 energies\n",
      "cost score: 5.430674582481957\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      " -0.86   5.43   1.39  13.64   0.39   1.16 weighted difference from target energies\n",
      "-15.57  11.43   9.61   1.82   0.16   0.16 energies\n",
      "cost score: 5.471058695647545\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.53   5.43   1.14  13.15   0.40   1.21 weighted difference from target energies\n",
      "-11.42  11.43   9.86   1.58   0.21   0.21 energies\n",
      "cost score: 5.473377059998188\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.28   5.46   0.97  12.84   0.47   1.40 weighted difference from target energies\n",
      "-12.16  11.46  10.03   1.42   0.40   0.40 energies\n",
      "cost score: 5.495307919468978\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.34   6.07   0.98  14.08   0.71   2.12 weighted difference from target energies\n",
      " -8.98  12.07  10.02   2.04   1.12   1.12 energies\n",
      "cost score: 6.104439169420033\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.98   6.25   2.25  17.01   0.33   0.98 weighted difference from target energies\n",
      "-10.05  12.25   8.75   3.50  -0.02  -0.02 energies\n",
      "cost score: 6.2830520850474\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.13   6.25   2.27  17.05   0.30   0.91 weighted difference from target energies\n",
      " -9.60  12.25   8.73   3.52  -0.09  -0.09 energies\n",
      "cost score: 6.282372953756301\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.93   7.27  -1.67  11.19  -0.04   1.90 weighted difference from target energies\n",
      " -7.21  13.27  12.67   0.60  -1.13   0.90 energies\n",
      "cost score: 7.275619544500768\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.91   7.17  -1.66  11.03  -0.05   1.89 weighted difference from target energies\n",
      " -7.27  13.17  12.66   0.52  -1.14   0.89 energies\n",
      "cost score: 7.1845001717531485\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.25   7.31  -1.26  12.10   0.99   2.97 weighted difference from target energies\n",
      " -6.24  13.31  12.26   1.05   1.97   1.97 energies\n",
      "cost score: 7.332464421878663\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.28  11.06  -5.15  11.83   1.01   3.03 weighted difference from target energies\n",
      " -6.16  17.06  16.15   0.91   2.03   2.03 energies\n",
      "cost score: 11.062273871734735\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.88   6.14   1.03  14.35   0.68   2.03 weighted difference from target energies\n",
      " -7.37  12.14   9.97   2.18   1.03   1.03 energies\n",
      "cost score: 6.183332316937137\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.30   6.15   1.15  14.59   0.64   1.92 weighted difference from target energies\n",
      " -6.10  12.15   9.85   2.30   0.92   0.92 energies\n",
      "cost score: 6.19378891282324\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.74   7.09  -1.13  11.91   1.11   3.33 weighted difference from target energies\n",
      " -4.78  13.09  12.13   0.96   2.33   2.33 energies\n",
      "cost score: 7.126763722986963\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.61   6.92   0.50  14.86   0.83   2.49 weighted difference from target energies\n",
      " -8.16  12.92  10.50   2.43   1.49   1.49 energies\n",
      "cost score: 6.945059879122918\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.25   7.36   2.25  19.22   0.58   1.74 weighted difference from target energies\n",
      " -9.24  13.36   8.75   4.61   0.74   0.74 energies\n",
      "cost score: 7.373774394441718\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.62   7.27   0.37  15.27   0.84   2.53 weighted difference from target energies\n",
      " -8.15  13.27  10.63   2.64   1.53   1.53 energies\n",
      "cost score: 7.280562527183771\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.61   7.36  -0.21  14.30   0.95   2.85 weighted difference from target energies\n",
      " -8.18  13.36  11.21   2.15   1.85   1.85 energies\n",
      "cost score: 7.371288897997711\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  2.31   8.00  -2.95  10.10  -0.10   4.08 weighted difference from target energies\n",
      " -6.08  14.00  13.95   0.05  -1.31   3.08 energies\n",
      "cost score: 8.023730290426206\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.83   7.80  -2.15  11.30  -0.11   3.02 weighted difference from target energies\n",
      " -7.51  13.80  13.15   0.65  -1.33   2.02 energies\n",
      "cost score: 7.810157418246129\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.98   7.71  -1.68  12.07  -0.00   3.35 weighted difference from target energies\n",
      " -7.07  13.71  12.68   1.04  -1.01   2.35 energies\n",
      "cost score: 7.728548097139301\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.81   7.34  -1.66  11.35   0.64   2.32 weighted difference from target energies\n",
      "-10.58  13.34  12.66   0.68   0.93   1.32 energies\n",
      "cost score: 7.347490941969903\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.76   7.29  -1.49  11.60   0.60   2.22 weighted difference from target energies\n",
      "-10.71  13.29  12.49   0.80   0.80   1.22 energies\n",
      "cost score: 7.2989095891147215\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.84   7.42  -1.84  11.15   0.68   2.36 weighted difference from target energies\n",
      "-10.48  13.42  12.84   0.57   1.04   1.36 energies\n",
      "cost score: 7.427203110064304\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.27   7.65  -3.70   7.90   1.04   3.13 weighted difference from target energies\n",
      " -9.20  13.65  14.70  -1.05   2.13   2.13 energies\n",
      "cost score: 7.6615970487378595\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  1.64   8.87  -2.36  13.04   0.63   1.90 weighted difference from target energies\n",
      " -8.08  14.87  13.36   1.52   0.90   0.90 energies\n",
      "cost score: 8.876645150007374\n",
      "run time in s: 340.64544105529785\n",
      "run time in min: 5.677424017588297\n"
     ]
    }
   ],
   "source": [
    "start= time.time()\n",
    "\n",
    "sRNA_kinetic, mRNA_kinetic, bestval_kinetic = run_optimize(1, model_rri, cost_kinetics, optimize=sa_optimize, EI=-15, EM=-7, verbose=True, steps=1000)\n",
    "end = time.time()\n",
    "print(f'run time in s: {end - start}')\n",
    "print(f'run time in min: {(end - start)/60}')\n",
    "\n",
    "# for accepted designs the sequence is printed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "01bdf73d-32fc-41c7-9eea-ccbf3e3d94ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best design\n",
      "sRNA: AACACAUCAGAUUUCCUGGUGUAACGAAUUUUUUAAGUGCUUCUUGCUUAAGCAAGUUUCAUCCCGACCCCCUCAGGGUCGGGAUUUUU\n",
      "mRNA: AUGUUAGACUACUGUUUGGCGGCCGUAUUUAAAGAUUUGUUACGCUGGGGAAUCGCGCUCGUUCGCAGCCAGCCGUAGAAAAGGCGAGUUCCGCUCCCGUAGUUCUACGCGUUCCGGUUAGGUAAGGGCGAGCGUGAUAGGAGCCCCGGUAUGAGUAAAGGAGAAGAACUUUUCACU\n",
      "Cost: 1.4458152091350438\n",
      "========================next design==================================\n",
      "bind, dG_bound, dG_free, dG_diff, seed, barrier\n",
      "  0.52  -0.71  -1.14  -3.71  -0.07  -0.20 weighted difference from target energies\n",
      "-11.44   5.29  12.14  -6.86  -1.20  -1.20 energies\n",
      "cost score: 1.4458152091350438\n",
      "designed mRNA\n",
      "AUGUUAGACUACUGUUUGGCGGCCGUAUUUAAAGAUUUGUUACGCUGGGGAAUCGCGCUCGUUCGCAGCCAGCCGUAGAAAAGGCGAGUUCCGCUCCCGUAGUUCUACGCGUUCCGGUUAGGUAAGGGCGAGCGUGAUAGGAGCCCCGGUAUGAGUAAAGGAGAAGAACUUUUCACU\n",
      "The overall cost score is 1.4458152091350438, it is computed from the following features (target energies in brackets):\n",
      "- free energy of the full interaction: -11.44 kcal/mol (-13 kcal/mol)\n",
      "- free energy of the barrier state: -1.2 kcal/mol (-1 kcal/mol)\n",
      "- free energy of 5bps seed from which the minimum barrier folding paths starts: -1.2 kcal/mol (-1 kcal/mol)\n",
      "- seed resulting in the minimum barrier state folding path starts at base pair 23\n",
      "- opening energy of the RBS+30nts when sRNA is bound: 5.288082122802734 kcal/mol (6 kcal/mol)\n",
      "- opening energy of the RBS+30nts when mRNA is free: 12.144622802734375 kcal/mol (11 kcal/mol)\n",
      "- change of the opening energy of the RBS+30nts when sRNA binds: -6.856540679931641 kcal/mol (-5 kcal/mol; currently not targeted)\n",
      "\n",
      "IntaRNA results:\n",
      "The interaction range on the sRNA is 13-40\n",
      "The interaction range on the mRNA is 25-51\n",
      "Base pair list: (13,51):(14,50):(15,49):(16,48):(17,47):(18,46):(19,45):(20,44):(21,43):(22,42):(23,41):(24,40):(25,39):(26,38):(27,37):(28,36):(30,35):(31,34):(32,33):(33,32):(34,31):(35,30):(36,29):(37,28):(38,27):(39,26):(40,25)\n",
      "E: -9.33, ED1: 9.2, ED2: 9.96, E_loops: -32.8\n"
     ]
    },
    {
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",
      "text/plain": [
       "<PIL.EpsImagePlugin.EpsImageFile image mode=RGB size=700x700>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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",
      "text/plain": [
       "<PIL.EpsImagePlugin.EpsImageFile image mode=RGB size=700x700>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Best design\")\n",
    "print('sRNA:', sRNA_kinetic)\n",
    "print('mRNA:', mRNA_kinetic)\n",
    "print('Cost:', bestval_kinetic)\n",
    "\n",
    "cost_kinetics(sRNA_kinetic, mRNA_kinetic, verbose =True, vverbose =True)\n",
    "\n",
    "'''\n",
    "i, j, k, l, be = rri.RNAup(mRNA_kinetic, sRNA_kinetic)\n",
    "print(\"Interaction prediction with RNAup for comaprison\")\n",
    "print(\"Binding region of rpos:\", (i, j))\n",
    "print(\"Binding region of rdsa:\", (k, l))\n",
    "print(\"Binding Energy:\", be, \"kcal/mol\")\n",
    "'''\n",
    "\n",
    "mRNA_unbound, sRNA_unbound = rri.prediction_unbound(mRNA_kinetic, sRNA_kinetic)\n",
    "rri.draw_RNAplot(sRNA_kinetic, mRNA_kinetic, sRNA_unbound, mRNA_unbound,output='unbound_kinetic_design.ps')\n",
    "mRNA_bound, sRNA_bound = rri.prediction_bound(mRNA_kinetic, sRNA_kinetic)\n",
    "rri.draw_RNAplot(sRNA_kinetic, mRNA_kinetic, sRNA_bound, mRNA_bound, output='bound_kinetic_design.ps')\n",
    "\n",
    "rri.plot_energylandscape(sRNA_kinetic, mRNA_kinetic, id1='DsrA', id2=\"designed mRNA (with kinetics)\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0a45cb1-390a-4cb2-95ab-41d2637fc5e7",
   "metadata": {},
   "source": [
    "### Kinetic cost function applied to rpoS-DsrA example and thermodynamic design for comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "eb6be0c4-3ebb-4d60-ae6f-336bc19003ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "designed mRNA\n",
      "CACCGGAACCAGUUCAACACGCUUGCAUUUUGAAAUUCGUUACAAGGGGAAAUCCGUAAACCCGCUGCGUUAUUUGCCGCAGCGAUAAAUCGGCGGAACCAGGCUUUUGCUUGAAUGUUCCGUCAAGGGAUCACGGGUAGGAGCCACCUUAUGAGUCAGAAUACGCUGAAAGUUCAU\n",
      "The overall cost score is 2.3847826956863036, it is computed from the following features (target energies in brackets):\n",
      "- free energy of the full interaction: -11.69 kcal/mol (-13 kcal/mol)\n",
      "- free energy of the barrier state: 0.68 kcal/mol (-1 kcal/mol)\n",
      "- free energy of 5bps seed from which the minimum barrier folding paths starts: 0.68 kcal/mol (-1 kcal/mol)\n",
      "- seed resulting in the minimum barrier state folding path starts at base pair 12\n",
      "- opening energy of the RBS+30nts when sRNA is bound: 6.337974548339844 kcal/mol (6 kcal/mol)\n",
      "- opening energy of the RBS+30nts when mRNA is free: 11.234672546386719 kcal/mol (11 kcal/mol)\n",
      "- change of the opening energy of the RBS+30nts when sRNA binds: -4.896697998046875 kcal/mol (-5 kcal/mol; currently not targeted)\n",
      "\n",
      "IntaRNA results:\n",
      "The interaction range on the sRNA is 10-40\n",
      "The interaction range on the mRNA is 25-54\n",
      "Base pair list: (10,54):(11,53):(12,52):(13,51):(14,50):(15,49):(16,48):(17,47):(20,44):(21,43):(22,42):(23,41):(24,40):(25,39):(26,38):(27,37):(28,36):(29,35):(30,34):(31,33):(32,32):(35,30):(36,29):(37,28):(38,27):(39,26):(40,25)\n",
      "E: -11.39, ED1: 9.22, ED2: 12.09, E_loops: -34.9\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2.3847826956863036"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cost_kinetics(dsra_seq, rpos_seq, verbose=False, vverbose=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "25d3a550-8fc9-4d16-90dc-8665ef7700d1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "designed mRNA\n",
      "UCCCUGAUUAACGAGUGGAGUGAUGCGUUUUGAAGUUCGUUACAGUAGGAGGUUUCAACGGUUGGUGUGGGGAAAAUCGACACAUCAGCCUGUGGUUAGGCGUUGACUGCGCUUACCCAUGGUCAGAACAGAUGGAGUAGGAGCCUUACUAUGAGUAAAGGAGAAGAACUUUUCACU\n",
      "The overall cost score is 3.798430123588564, it is computed from the following features (target energies in brackets):\n",
      "- free energy of the full interaction: -7.2 kcal/mol (-13 kcal/mol)\n",
      "- free energy of the barrier state: 2.07 kcal/mol (-1 kcal/mol)\n",
      "- free energy of 5bps seed from which the minimum barrier folding paths starts: 1.39 kcal/mol (-1 kcal/mol)\n",
      "- seed resulting in the minimum barrier state folding path starts at base pair 14\n",
      "- opening energy of the RBS+30nts when sRNA is bound: 8.635135650634766 kcal/mol (6 kcal/mol)\n",
      "- opening energy of the RBS+30nts when mRNA is free: 15.319305419921875 kcal/mol (11 kcal/mol)\n",
      "- change of the opening energy of the RBS+30nts when sRNA binds: -6.684169769287109 kcal/mol (-5 kcal/mol; currently not targeted)\n",
      "\n",
      "IntaRNA results:\n",
      "The interaction range on the sRNA is 9-32\n",
      "The interaction range on the mRNA is 32-55\n",
      "Base pair list: (9,55):(10,54):(11,53):(12,52):(13,51):(14,50):(15,49):(16,48):(17,47):(18,46):(20,44):(21,43):(22,42):(23,41):(24,40):(25,39):(26,38):(27,37):(28,36):(29,35):(30,34):(31,33):(32,32)\n",
      "E: -6.81, ED1: 8.64, ED2: 12.66, E_loops: -32.5\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "3.798430123588564"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cost_kinetics(sRNA_design, mRNA_design, verbose=False, vverbose=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "38056615-caa7-4aa7-bdd6-e1804242dcbb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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