Open a terminal
window and navigate to the folder where you want to
install HADDOCK3; for example: software
. The current installation
instructions are local and will affect only your user.
Before starting with the installation of HADDOCK3, make sure to properly install CNS. If you have installed a previous version of HADDOCK, you may already have a suitable version of CNS. Please do check your CNS installation before proceeding.
Mind the --recursive
flag when cloning!
git clone --recursive https://github.com/haddocking/haddock3.git
cd haddock3
cd src/fcc/src
chmod u+x Makefile
make
cd -
By the end of the above commands, you should be back to the haddock3
main folder.
You can use Python's venv
or Anaconda depending on your choice.
Commands are provided below:
virtualenv venv --python=3.9
source venv/bin/activate
pip install -r requirements.txt
conda env create -f requirements.yml
conda activate haddock3
python setup.py develop --no-deps
mkdir -p bin/
# on mac
ln -s /PATH/TO/cns_solve_1.3/mac-intel-darwin/source/cns_solve-2206031450.exe bin/cns
# on linux
ln -s /PATH/TO/cns_solve_1.3/intel-x86_64bit-linux/source/cns_solve-2002171359.exe bin/cns
As long as you have the HADDOCK3 python environment activated, you can navigate away from the HADDOCK3 installation folder. You can run HADDOCK3 from anywhere. To run HADDOCK3, follow the usage guidelines.
Navigate to the haddock3
installation folder (the one you cloned from
GitHub). Ensure you have the haddock3
python environment activated.
Please consider HADDOCK3 is under active development, as well as its
dependencies. If the updating processing fails, it is safe to reinstall
from scratch. Always refer to the latest installation guidelines.
# if you used `venv`
source venv/bin/activate
# if you used `conda`
conda activate haddock3
Afterwards:
# pull the latest source code from our repository to your computer
git pull
# if you used venv to create the python environment, run:
pip install -r requirements.txt --upgrade
# if you used anaconda to create the python environment, run:
conda env update -f requirements.yml
# ensure all command-lines clients are installed
python setup.py develop --no-deps
To use the mpi implementation of haddock3 you must have mpi4py installed in the haddock3 python environment, and OpenMPI in the host system.
$ pip install mpi4py
# or
$ conda install -c conda-forge mpi4py
Later, you can find here instructions on how to run HADDOCK3 with MPI.
HADDOCK3 can integrate third-party software in its workflows. However, we are not responsible for the proper installation of such packages, but we help you install them. Below, you will find a list of all third-party packages HADDOCK3 can use and guidelines for their proper installation.
To install to lightdock follow the instructions in the project's website. Remember to install it under the same Python environment you created for HADDOCK3. If you have any doubts, please let us know.
- Clone the latest version:
cd some-folder
git clone https://github.com/rvhonorato/gdock.git
- Install Python3+ dependencies
pip install deap scipy mgzip biopython
- Set
GDOCK_PATH
export GDOCK_PATH=some-folder
Important: These are not the full gdock
's installation
instructions as here only the model generation is used. Please check the
repository page for more
information.