data_collection.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
      "                                 Dload  Upload   Total   Spent    Left  Speed\n",
      "\n",
      "  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0\n",
      "  0     0    0     0    0     0      0      0 --:--:--  0:00:01 --:--:--     0\n",
      "  0     0    0     0    0     0      0      0 --:--:--  0:00:02 --:--:--     0\n",
      "  0     0    0     0    0     0      0      0 --:--:--  0:00:03 --:--:--     0\n",
      "  0     0    0     0    0     0      0      0 --:--:--  0:00:04 --:--:--     0\n",
      "  0     0    0     0    0     0      0      0 --:--:--  0:00:05 --:--:--     0\n",
      "  0 80.5M    0     0    0     0      0      0 --:--:--  0:00:06 --:--:--     0\n",
      "  0 80.5M    0  512k    0     0  87421      0  0:16:06  0:00:06  0:16:00  110k\n",
      "  3 80.5M    3 2896k    0     0   413k      0  0:03:19  0:00:07  0:03:12  622k\n",
      "  7 80.5M    7 6240k    0     0   780k      0  0:01:45  0:00:08  0:01:37 1349k\n",
      " 10 80.5M   10 8944k    0     0   993k      0  0:01:23  0:00:09  0:01:14 1933k\n",
      " 13 80.5M   13 10.7M    0     0  1099k      0  0:01:15  0:00:10  0:01:05 2376k\n",
      " 16 80.5M   16 12.9M    0     0  1205k      0  0:01:08  0:00:11  0:00:57 2550k\n",
      " 17 80.5M   17 14.4M    0     0  1234k      0  0:01:06  0:00:12  0:00:54 2391k\n",
      " 21 80.5M   21 17.2M    0     0  1357k      0  0:01:00  0:00:13  0:00:47 2281k\n",
      " 25 80.5M   25 20.4M    0     0  1496k      0  0:00:55  0:00:14  0:00:41 2400k\n",
      " 29 80.5M   29 23.7M    0     0  1622k      0  0:00:50  0:00:15  0:00:35 2668k\n",
      " 32 80.5M   32 26.1M    0     0  1671k      0  0:00:49  0:00:16  0:00:33 2694k\n",
      " 36 80.5M   36 29.0M    0     0  1751k      0  0:00:47  0:00:17  0:00:30 2992k\n",
      " 39 80.5M   39 32.0M    0     0  1824k      0  0:00:45  0:00:18  0:00:27 3036k\n",
      " 43 80.5M   43 34.9M    0     0  1882k      0  0:00:43  0:00:19  0:00:24 2930k\n",
      " 45 80.5M   45 36.8M    0     0  1887k      0  0:00:43  0:00:20  0:00:23 2681k\n",
      " 48 80.5M   48 38.8M    0     0  1894k      0  0:00:43  0:00:21  0:00:22 2611k\n",
      " 50 80.5M   50 40.5M    0     0  1805k      0  0:00:45  0:00:23  0:00:22 2207k\n",
      " 51 80.5M   51 41.4M    0     0  1845k      0  0:00:44  0:00:23  0:00:21 1917k\n",
      " 51 80.5M   51 41.8M    0     0  1713k      0  0:00:48  0:00:25  0:00:23 1328k\n",
      " 52 80.5M   52 42.0M    0     0  1654k      0  0:00:49  0:00:26  0:00:23  996k\n",
      " 52 80.5M   52 42.1M    0     0  1597k      0  0:00:51  0:00:27  0:00:24  648k\n",
      " 52 80.5M   52 42.1M    0     0  1540k      0  0:00:53  0:00:28  0:00:25  330k\n",
      " 52 80.5M   52 42.1M    0     0  1489k      0  0:00:55  0:00:29  0:00:26  132k\n",
      " 52 80.5M   52 42.1M    0     0  1440k      0  0:00:57  0:00:30  0:00:27 72649\n",
      " 52 80.5M   52 42.2M    0     0  1443k      0  0:00:57  0:00:30  0:00:27 61684\n",
      " 52 80.5M   52 42.5M    0     0  1406k      0  0:00:58  0:00:31  0:00:27   99k\n",
      " 54 80.5M   54 44.2M    0     0  1417k      0  0:00:58  0:00:32  0:00:26  457k\n",
      " 57 80.5M   57 46.5M    0     0  1443k      0  0:00:57  0:00:33  0:00:24 1027k\n",
      " 58 80.5M   58 46.9M    0     0  1413k      0  0:00:58  0:00:34  0:00:24 1084k\n",
      " 61 80.5M   61 49.8M    0     0  1459k      0  0:00:56  0:00:35  0:00:21 1574k\n",
      " 64 80.5M   64 51.9M    0     0  1476k      0  0:00:55  0:00:36  0:00:19 1910k\n",
      " 66 80.5M   66 53.9M    0     0  1491k      0  0:00:55  0:00:37  0:00:18 1971k\n",
      " 69 80.5M   69 56.2M    0     0  1514k      0  0:00:54  0:00:38  0:00:16 1984k\n",
      " 71 80.5M   71 57.7M    0     0  1478k      0  0:00:55  0:00:40  0:00:15 2096k\n",
      " 71 80.5M   71 57.7M    0     0  1442k      0  0:00:57  0:00:41  0:00:16 1576k\n",
      " 73 80.5M   73 59.2M    0     0  1479k      0  0:00:55  0:00:41  0:00:14 1497k\n",
      " 77 80.5M   77 62.2M    0     0  1518k      0  0:00:54  0:00:42  0:00:12 1715k\n",
      " 81 80.5M   81 65.3M    0     0  1557k      0  0:00:52  0:00:43  0:00:09 1881k\n",
      " 84 80.5M   84 68.3M    0     0  1591k      0  0:00:51  0:00:44  0:00:07 2327k\n",
      " 87 80.5M   87 70.2M    0     0  1599k      0  0:00:51  0:00:45  0:00:06 2628k\n",
      " 88 80.5M   88 71.7M    0     0  1562k      0  0:00:52  0:00:47  0:00:05 2308k\n",
      " 89 80.5M   89 71.7M    0     0  1531k      0  0:00:53  0:00:48  0:00:05 1906k\n",
      " 92 80.5M   92 74.5M    0     0  1589k      0  0:00:51  0:00:48  0:00:03 1868k\n",
      " 96 80.5M   96 78.0M    0     0  1630k      0  0:00:50  0:00:49  0:00:01 1974k\n",
      " 99 80.5M   99 80.5M    0     0  1617k      0  0:00:51  0:00:51 --:--:-- 1898k\n",
      "100 80.5M  100 80.5M    0     0  1617k      0  0:00:51  0:00:51 --:--:-- 2261k\n"
     ]
    }
   ],
   "source": [
    "! curl.exe --output dataset_v1.csv --url https://media.githubusercontent.com/media/molecularsets/moses/master/data/dataset_v1.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('dataset_v1.csv')\n",
    "df = df[df['SPLIT'] == 'train']\n",
    "df['IC50'] = len(df['SMILES']) * [\"\"]\n",
    "df.to_csv('train_moses_1.csv', index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1584663"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df[\"SMILES\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\mored\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3146: DtypeWarning: Columns (1,3,4,5) have mixed types.Specify dtype option on import or set low_memory=False.\n",
      "  has_raised = await self.run_ast_nodes(code_ast.body, cell_name,\n"
     ]
    }
   ],
   "source": [
    "df = pd.read_csv('menthionyl.csv', sep=';')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "ic50 = df[df[\"Standard Units\"] != \"%\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "ename": "PermissionError",
     "evalue": "[Errno 13] Permission denied: 'ic50-methionyl.csv'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mPermissionError\u001b[0m                           Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-41-02965a743e09>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mic50\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'ic50-methionyl.csv'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36mto_csv\u001b[1;34m(self, path_or_buf, sep, na_rep, float_format, columns, header, index, index_label, mode, encoding, compression, quoting, quotechar, line_terminator, chunksize, date_format, doublequote, escapechar, decimal, errors, storage_options)\u001b[0m\n\u001b[0;32m   3382\u001b[0m         )\n\u001b[0;32m   3383\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3384\u001b[1;33m         return DataFrameRenderer(formatter).to_csv(\n\u001b[0m\u001b[0;32m   3385\u001b[0m             \u001b[0mpath_or_buf\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3386\u001b[0m             \u001b[0mline_terminator\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mline_terminator\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\pandas\\io\\formats\\format.py\u001b[0m in \u001b[0;36mto_csv\u001b[1;34m(self, path_or_buf, encoding, sep, columns, index_label, mode, compression, quoting, quotechar, line_terminator, chunksize, date_format, doublequote, escapechar, errors, storage_options)\u001b[0m\n\u001b[0;32m   1081\u001b[0m             \u001b[0mformatter\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfmt\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1082\u001b[0m         )\n\u001b[1;32m-> 1083\u001b[1;33m         \u001b[0mcsv_formatter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msave\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1084\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1085\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mcreated_buffer\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\pandas\\io\\formats\\csvs.py\u001b[0m in \u001b[0;36msave\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    226\u001b[0m         \"\"\"\n\u001b[0;32m    227\u001b[0m         \u001b[1;31m# apply compression and byte/text conversion\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 228\u001b[1;33m         with get_handle(\n\u001b[0m\u001b[0;32m    229\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    230\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\pandas\\io\\common.py\u001b[0m in \u001b[0;36mget_handle\u001b[1;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[0;32m    637\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mioargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mencoding\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;34m\"b\"\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mioargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    638\u001b[0m             \u001b[1;31m# Encoding\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 639\u001b[1;33m             handle = open(\n\u001b[0m\u001b[0;32m    640\u001b[0m                 \u001b[0mhandle\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    641\u001b[0m                 \u001b[0mioargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mPermissionError\u001b[0m: [Errno 13] Permission denied: 'ic50-methionyl.csv'"
     ]
    }
   ],
   "source": [
    "ic50.to_csv('ic50-methionyl.csv', index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\mored\\Miniconda3\\envs\\leishnn\\lib\\site-packages\\pandas\\core\\indexing.py:1675: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._setitem_single_column(ilocs[0], value, pi)\n"
     ]
    }
   ],
   "source": [
    "ic50.loc[:,\"IC50\"] = [-math.log(x/max(list(ic50[\"Standard Value\"]))) for x in ic50[\"Standard Value\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "ic50.to_csv('train_ic50_3.csv', index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Molecule ChEMBL ID</th>\n",
       "      <th>Molecule Name</th>\n",
       "      <th>Molecule Max Phase</th>\n",
       "      <th>Molecular Weight</th>\n",
       "      <th>#RO5 Violations</th>\n",
       "      <th>AlogP</th>\n",
       "      <th>Compound Key</th>\n",
       "      <th>Smiles</th>\n",
       "      <th>Standard Type</th>\n",
       "      <th>Standard Relation</th>\n",
       "      <th>...</th>\n",
       "      <th>Target ChEMBL ID</th>\n",
       "      <th>Target Name</th>\n",
       "      <th>Target Organism</th>\n",
       "      <th>Target Type</th>\n",
       "      <th>Document ChEMBL ID</th>\n",
       "      <th>Source ID</th>\n",
       "      <th>Source Description</th>\n",
       "      <th>Document Journal</th>\n",
       "      <th>Document Year</th>\n",
       "      <th>Cell ChEMBL ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CHEMBL497305</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>426.300000</td>\n",
       "      <td>1</td>\n",
       "      <td>5.56</td>\n",
       "      <td>NXN-6</td>\n",
       "      <td>O=C(O)[C@@H]1c2ccccc2C(=O)N(Cc2ccc(Cl)cc2)[C@H...</td>\n",
       "      <td>Kd</td>\n",
       "      <td>'='</td>\n",
       "      <td>...</td>\n",
       "      <td>CHEMBL5023</td>\n",
       "      <td>p53-binding protein Mdm-2</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>SINGLE PROTEIN</td>\n",
       "      <td>CHEMBL1156625</td>\n",
       "      <td>1</td>\n",
       "      <td>Scientific Literature</td>\n",
       "      <td>J. Med. Chem.</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CHEMBL212747</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>637.350000</td>\n",
       "      <td>2</td>\n",
       "      <td>5.86</td>\n",
       "      <td>31</td>\n",
       "      <td>CN(C)CCCN1C(=O)[C@H](c2ccc(Cl)cc2)N(Cc2ccc(Cl)...</td>\n",
       "      <td>IC50</td>\n",
       "      <td>'='</td>\n",
       "      <td>...</td>\n",
       "      <td>CHEMBL5023</td>\n",
       "      <td>p53-binding protein Mdm-2</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>SINGLE PROTEIN</td>\n",
       "      <td>CHEMBL1138098</td>\n",
       "      <td>1</td>\n",
       "      <td>Scientific Literature</td>\n",
       "      <td>Bioorg. Med. Chem. Lett.</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CHEMBL212568</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>664.370000</td>\n",
       "      <td>2</td>\n",
       "      <td>5.97</td>\n",
       "      <td>25</td>\n",
       "      <td>Cc1cc(Cl)ccc1CN1C(=O)c2cc(I)ccc2N(CCN2CCOCC2)C...</td>\n",
       "      <td>IC50</td>\n",
       "      <td>'='</td>\n",
       "      <td>...</td>\n",
       "      <td>CHEMBL5023</td>\n",
       "      <td>p53-binding protein Mdm-2</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>SINGLE PROTEIN</td>\n",
       "      <td>CHEMBL1138098</td>\n",
       "      <td>1</td>\n",
       "      <td>Scientific Literature</td>\n",
       "      <td>Bioorg. Med. Chem. Lett.</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CHEMBL424876</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>655.320000</td>\n",
       "      <td>2</td>\n",
       "      <td>5.70</td>\n",
       "      <td>49</td>\n",
       "      <td>COCCOCCN1C(=O)[C@H](c2ccc(Cl)cc2)N(Cc2ccc(Cl)c...</td>\n",
       "      <td>IC50</td>\n",
       "      <td>'='</td>\n",
       "      <td>...</td>\n",
       "      <td>CHEMBL5023</td>\n",
       "      <td>p53-binding protein Mdm-2</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>SINGLE PROTEIN</td>\n",
       "      <td>CHEMBL1138098</td>\n",
       "      <td>1</td>\n",
       "      <td>Scientific Literature</td>\n",
       "      <td>Bioorg. Med. Chem. Lett.</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CHEMBL555017</td>\n",
       "      <td>GAMBOGIC ACID</td>\n",
       "      <td>0</td>\n",
       "      <td>628.760000</td>\n",
       "      <td>2</td>\n",
       "      <td>7.24</td>\n",
       "      <td>2</td>\n",
       "      <td>CC(C)=CCC[C@]1(C)C=Cc2c(O)c3c(c(CC=C(C)C)c2O1)...</td>\n",
       "      <td>Inhibition</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>CHEMBL5023</td>\n",
       "      <td>p53-binding protein Mdm-2</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>SINGLE PROTEIN</td>\n",
       "      <td>CHEMBL2331232</td>\n",
       "      <td>1</td>\n",
       "      <td>Scientific Literature</td>\n",
       "      <td>J. Nat. Prod.</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3221</th>\n",
       "      <td>CHEMBL4276740</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>614.68</td>\n",
       "      <td>1</td>\n",
       "      <td>2.05</td>\n",
       "      <td>34*</td>\n",
       "      <td>CN[C@@H](C)C(=O)N[C@@H](CNC(=O)c1ccc(S(=O)(=O)...</td>\n",
       "      <td>Activity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>CHEMBL4198</td>\n",
       "      <td>Inhibitor of apoptosis protein 3</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>SINGLE PROTEIN</td>\n",
       "      <td>CHEMBL4251755</td>\n",
       "      <td>1</td>\n",
       "      <td>Scientific Literature</td>\n",
       "      <td>J Med Chem</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3222</th>\n",
       "      <td>CHEMBL4286443</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>214.27</td>\n",
       "      <td>0</td>\n",
       "      <td>2.50</td>\n",
       "      <td>3c</td>\n",
       "      <td>Cc1cccc(C(=O)n2nc(C)cc2C)c1</td>\n",
       "      <td>IC50</td>\n",
       "      <td>'='</td>\n",
       "      <td>...</td>\n",
       "      <td>CHEMBL4198</td>\n",
       "      <td>Inhibitor of apoptosis protein 3</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>SINGLE PROTEIN</td>\n",
       "      <td>CHEMBL4270558</td>\n",
       "      <td>1</td>\n",
       "      <td>Scientific Literature</td>\n",
       "      <td>Eur J Med Chem</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3223</th>\n",
       "      <td>CHEMBL4276715</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>433.53</td>\n",
       "      <td>0</td>\n",
       "      <td>0.36</td>\n",
       "      <td>26</td>\n",
       "      <td>CN[C@@H](C)C(=O)N[C@@H](CCN)C(=O)N1CCC[C@@H]1C...</td>\n",
       "      <td>IC50</td>\n",
       "      <td>'='</td>\n",
       "      <td>...</td>\n",
       "      <td>CHEMBL4198</td>\n",
       "      <td>Inhibitor of apoptosis protein 3</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>SINGLE PROTEIN</td>\n",
       "      <td>CHEMBL4251755</td>\n",
       "      <td>1</td>\n",
       "      <td>Scientific Literature</td>\n",
       "      <td>J Med Chem</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3224</th>\n",
       "      <td>CHEMBL4291873</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>565.61</td>\n",
       "      <td>1</td>\n",
       "      <td>2.74</td>\n",
       "      <td>28</td>\n",
       "      <td>CN[C@@H](C)C(=O)N[C@@H](Cc1ccc(CP(=O)(O)O)cc1)...</td>\n",
       "      <td>IC50</td>\n",
       "      <td>'='</td>\n",
       "      <td>...</td>\n",
       "      <td>CHEMBL4198</td>\n",
       "      <td>Inhibitor of apoptosis protein 3</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>SINGLE PROTEIN</td>\n",
       "      <td>CHEMBL4251755</td>\n",
       "      <td>1</td>\n",
       "      <td>Scientific Literature</td>\n",
       "      <td>J Med Chem</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3225</th>\n",
       "      <td>CHEMBL4281278</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>614.68</td>\n",
       "      <td>1</td>\n",
       "      <td>2.05</td>\n",
       "      <td>34</td>\n",
       "      <td>CN[C@@H](C)C(=O)N[C@@H](CNC(=O)c1ccc(S(=O)(=O)...</td>\n",
       "      <td>IC50</td>\n",
       "      <td>'='</td>\n",
       "      <td>...</td>\n",
       "      <td>CHEMBL4198</td>\n",
       "      <td>Inhibitor of apoptosis protein 3</td>\n",
       "      <td>Homo sapiens</td>\n",
       "      <td>SINGLE PROTEIN</td>\n",
       "      <td>CHEMBL4251755</td>\n",
       "      <td>1</td>\n",
       "      <td>Scientific Literature</td>\n",
       "      <td>J Med Chem</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14108 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Molecule ChEMBL ID  Molecule Name  Molecule Max Phase Molecular Weight  \\\n",
       "0          CHEMBL497305            NaN                   0       426.300000   \n",
       "1          CHEMBL212747            NaN                   0       637.350000   \n",
       "2          CHEMBL212568            NaN                   0       664.370000   \n",
       "3          CHEMBL424876            NaN                   0       655.320000   \n",
       "4          CHEMBL555017  GAMBOGIC ACID                   0       628.760000   \n",
       "...                 ...            ...                 ...              ...   \n",
       "3221      CHEMBL4276740            NaN                   0           614.68   \n",
       "3222      CHEMBL4286443            NaN                   0           214.27   \n",
       "3223      CHEMBL4276715            NaN                   0           433.53   \n",
       "3224      CHEMBL4291873            NaN                   0           565.61   \n",
       "3225      CHEMBL4281278            NaN                   0           614.68   \n",
       "\n",
       "     #RO5 Violations AlogP Compound Key  \\\n",
       "0                  1  5.56        NXN-6   \n",
       "1                  2  5.86           31   \n",
       "2                  2  5.97           25   \n",
       "3                  2  5.70           49   \n",
       "4                  2  7.24            2   \n",
       "...              ...   ...          ...   \n",
       "3221               1  2.05          34*   \n",
       "3222               0  2.50           3c   \n",
       "3223               0  0.36           26   \n",
       "3224               1  2.74           28   \n",
       "3225               1  2.05           34   \n",
       "\n",
       "                                                 Smiles Standard Type  \\\n",
       "0     O=C(O)[C@@H]1c2ccccc2C(=O)N(Cc2ccc(Cl)cc2)[C@H...            Kd   \n",
       "1     CN(C)CCCN1C(=O)[C@H](c2ccc(Cl)cc2)N(Cc2ccc(Cl)...          IC50   \n",
       "2     Cc1cc(Cl)ccc1CN1C(=O)c2cc(I)ccc2N(CCN2CCOCC2)C...          IC50   \n",
       "3     COCCOCCN1C(=O)[C@H](c2ccc(Cl)cc2)N(Cc2ccc(Cl)c...          IC50   \n",
       "4     CC(C)=CCC[C@]1(C)C=Cc2c(O)c3c(c(CC=C(C)C)c2O1)...    Inhibition   \n",
       "...                                                 ...           ...   \n",
       "3221  CN[C@@H](C)C(=O)N[C@@H](CNC(=O)c1ccc(S(=O)(=O)...      Activity   \n",
       "3222                        Cc1cccc(C(=O)n2nc(C)cc2C)c1          IC50   \n",
       "3223  CN[C@@H](C)C(=O)N[C@@H](CCN)C(=O)N1CCC[C@@H]1C...          IC50   \n",
       "3224  CN[C@@H](C)C(=O)N[C@@H](Cc1ccc(CP(=O)(O)O)cc1)...          IC50   \n",
       "3225  CN[C@@H](C)C(=O)N[C@@H](CNC(=O)c1ccc(S(=O)(=O)...          IC50   \n",
       "\n",
       "     Standard Relation  ...  Target ChEMBL ID  \\\n",
       "0                  '='  ...        CHEMBL5023   \n",
       "1                  '='  ...        CHEMBL5023   \n",
       "2                  '='  ...        CHEMBL5023   \n",
       "3                  '='  ...        CHEMBL5023   \n",
       "4                  NaN  ...        CHEMBL5023   \n",
       "...                ...  ...               ...   \n",
       "3221               NaN  ...        CHEMBL4198   \n",
       "3222               '='  ...        CHEMBL4198   \n",
       "3223               '='  ...        CHEMBL4198   \n",
       "3224               '='  ...        CHEMBL4198   \n",
       "3225               '='  ...        CHEMBL4198   \n",
       "\n",
       "                           Target Name  Target Organism     Target Type  \\\n",
       "0            p53-binding protein Mdm-2     Homo sapiens  SINGLE PROTEIN   \n",
       "1            p53-binding protein Mdm-2     Homo sapiens  SINGLE PROTEIN   \n",
       "2            p53-binding protein Mdm-2     Homo sapiens  SINGLE PROTEIN   \n",
       "3            p53-binding protein Mdm-2     Homo sapiens  SINGLE PROTEIN   \n",
       "4            p53-binding protein Mdm-2     Homo sapiens  SINGLE PROTEIN   \n",
       "...                                ...              ...             ...   \n",
       "3221  Inhibitor of apoptosis protein 3     Homo sapiens  SINGLE PROTEIN   \n",
       "3222  Inhibitor of apoptosis protein 3     Homo sapiens  SINGLE PROTEIN   \n",
       "3223  Inhibitor of apoptosis protein 3     Homo sapiens  SINGLE PROTEIN   \n",
       "3224  Inhibitor of apoptosis protein 3     Homo sapiens  SINGLE PROTEIN   \n",
       "3225  Inhibitor of apoptosis protein 3     Homo sapiens  SINGLE PROTEIN   \n",
       "\n",
       "     Document ChEMBL ID Source ID     Source Description  \\\n",
       "0         CHEMBL1156625         1  Scientific Literature   \n",
       "1         CHEMBL1138098         1  Scientific Literature   \n",
       "2         CHEMBL1138098         1  Scientific Literature   \n",
       "3         CHEMBL1138098         1  Scientific Literature   \n",
       "4         CHEMBL2331232         1  Scientific Literature   \n",
       "...                 ...       ...                    ...   \n",
       "3221      CHEMBL4251755         1  Scientific Literature   \n",
       "3222      CHEMBL4270558         1  Scientific Literature   \n",
       "3223      CHEMBL4251755         1  Scientific Literature   \n",
       "3224      CHEMBL4251755         1  Scientific Literature   \n",
       "3225      CHEMBL4251755         1  Scientific Literature   \n",
       "\n",
       "              Document Journal Document Year Cell ChEMBL ID  \n",
       "0                J. Med. Chem.        2008.0           None  \n",
       "1     Bioorg. Med. Chem. Lett.        2006.0           None  \n",
       "2     Bioorg. Med. Chem. Lett.        2006.0           None  \n",
       "3     Bioorg. Med. Chem. Lett.        2006.0           None  \n",
       "4                J. Nat. Prod.        2013.0           None  \n",
       "...                        ...           ...            ...  \n",
       "3221                J Med Chem        2018.0           None  \n",
       "3222            Eur J Med Chem        2018.0           None  \n",
       "3223                J Med Chem        2018.0           None  \n",
       "3224                J Med Chem        2018.0           None  \n",
       "3225                J Med Chem        2018.0           None  \n",
       "\n",
       "[14108 rows x 41 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ligase = pd.read_csv('ligase (1).csv', sep=';')\n",
    "for i in range(4):\n",
    "    new_lig = pd.read_csv(f\"ligase ({i+2}).csv\", sep=';')\n",
    "    ligase = pd.concat([ligase,new_lig])\n",
    "ligase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "ligase = pd.concat([df[df[\"Standard Units\"] == \"%\"], ligase])\n",
    "ligase[\"IC50\"] = len(ligase)*[\"\"]\n",
    "ligase.to_csv('train_ligase_2.csv', index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1303"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('train_ic50_3_filtered.csv')\n",
    "len(df)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}