liGAN is a PyTorch project for structure-based drug discovery with deep generative models of atomic density grids.
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CVAE journal paper (under review)
NOTE: Please be aware that the current version of molgrid provided through pip/conda is incompatible with conda openbabel, and you will likely get segmentation faults if you install them both through conda.
A molgrid conda build recipe is in the works (see https://github.com/mattragoza/conda-molgrid), but for now you can use this environment to build libmolgrid from source.
To generate molecules, you must first download the pretrained model weights:
sh download_weights.sh
Then just run the generate.py script with the default configuration file:
python generate.py config/generate.config
To train a model from scratch, you must first download the full Crossdocked2020 data set:
sh download_data.sh
More info about this data set can be found here.
Then you can run the train.py script with the default configuration file:
python train.py config/train.config