OpenChem is a deep learning toolkit for Computational Chemistry with PyTorch backend. The goal of OpenChem is to make Deep Learning models an easy-to-use tool for Computational Chemistry and Drug Design Researchers.
Check out OpenChem documentation here.
We are working on populating OpenChem with more models and other building blocks.
In order to get started you need:
If you installed your Python with Anaconda you can run the following commands to get started:
git clone https://github.com/Mariewelt/OpenChem.git
cd OpenChem
conda create --name OpenChem python=3.7
conda activate OpenChem
conda install --yes --file requirements.txt
conda install -c rdkit rdkit nox cairo
conda install pytorch torchvision -c pytorch
pip install -e .
If your CUDA version is older than 9.0, check Pytorch website for different installation instructions.
Alternative way of installation is with Docker. We provide a Dockerfile, so you can run your models in a container that already has all the necessary packages installed. You will also need nvidia-docker in order to run models on GPU.
If you use OpenChem in your projects, please cite:
Korshunova, Maria, et al. "OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design." Journal of Chemical Information and Modeling 61.1 (2021): 7-13.
MolecularRNN model paper:
Popova, Mariya, et al. "MolecularRNN: Generating realistic molecular graphs with optimized properties." arXiv preprint arXiv:1905.13372 (2019).
OpenChem was supported by Carnegie Mellon University, the University of North Carolina at Chapel Hill and NVIDIA Corp.