Proximity Graph Networks: Predicting ligand affinity with Message Passing Neural Networks
Project description
torch_pgn
Proximity Graph Networks (torch_pgn) is a pytorch toolkit allowing for the modular application of multiple different encoder architectures to cheminformatic tasks centered around protein-ligand complexes.
Installation
torch-pgn either be installed from PyPi using the pip command or from source. We assume that all users are using conda, if you do not have conda, please install Miniconda from https://conda.io/miniconda.html.
Installation using pip
conda create --name torch_pgn python=3.7
conda activate torch_pgn
pip install torch_pgn
conda install pytorch-sparse -c pyg
conda install -c conda-forge openbabel
[!NOTE] If you are using a gpu machine and run into issues with this installation method we suggest you remove pytorch and pyg and reinstall using conda as follows:
conda remove pytorch
conda remove pyg
conda install pytorch
conda install pyg -c pyg
conda install pytorch-sparse -c pyg
Installation from source
git clone https://github.com/keiserlab/torch_pgn/torch_pgn.git
cd torch_pgn
conda env create -f environment.yml
conda activate torch_pgn
pip install -e
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