Geometry-based Molecular Generation with Deep Constrained Variational Autoencoder.
This is the official code implementation of GEOM-CVAE paper.
Acknowledgements
We thank the authors of Shape-Based Generative Modeling for de Novo Drug Design[1] for releasing their code. The code in this repository is based on their source code release. If you find this code useful, please consider citing their work.
Requirements
This code was tested in Python 3.6.8 with torch 1.7.1, torch-geometric 1.6.3, torch-scatter 2.0.6 and torch-sparse 0.6.9.
Datasets
The AID1706 Bioassay data for COVID-19 in PubChem database (https://pubchem.ncbi.nlm.nih.gov/bioassay/1706).
Reference:
[1]. @article{Miha2019Shapebased,
author = {Skalic, Miha and Jim\'{e}nez, Jos\'{e} and Sabbadin, Davide and Fabritiis, Gianni De},
title = {Shape-Based Generative Modeling for de Novo Drug Design},
journal = {Journal of Chemical Information and Modeling},
volume = {59},
number = {3},
pages = {1205-1214},
year = {2019}
}