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
andprepare_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 ===============================