Installation

1. Get sources from the GithubRepo

The sources for Docking Python can be downloaded from the GithubRepo.

You can either clone the public repository:

$ git clone git://github.com/samuelmurail/docking_py

Or download the tarball:

$ curl -OJL https://github.com/samuelmurail/docking_py/tarball/master

Once you have a copy of the source, switch to the docking_py directorie.

cd docking_py

2. Create Conda Environment

You need to create a conda environment to be able to use:

  • vina
  • smina
  • qvina2 and qvinaw
  • MGLTools for prepare_ligand4.py and prepare_receptor4.py scripts.
  • Autodock with or without GPU support

Use conda en create to create it using the .conda.yml file. You can overide the environmnent name using the option --name YOUR_NAME.

$ conda env create -f .conda.yml

If you use a linux OS and have a GPU card, you could try the autodock-gpu version:

$ conda env create -f .conda_gpu.yml

This will create an environmnet called docking or docking_gpu (or the name you defined). You will then, need to activate the environmnent:

$ conda activate docking

3. Install docking_py

Once you have a copy of the source and have create a conda encironment, you can install it with:

$ python setup.py install

4. Test Installation

To test the installation, simply use pytest:

$ pytest
==================================== test session starts ====================================
platform linux -- Python 3.8.2, pytest-5.4.2, py-1.9.0, pluggy-0.13.1
rootdir: /home/murail/Documents/Code/docking_py, inifile: pytest.ini
plugins: cov-2.10.1
collected 13 items

docking_py/docking.py .......                                                         [ 53%]
docking_py/tests/test_docking_py.py ......                                            [100%]

============================== 13 passed, 1 warning in 21.18s ===============================