microsoft/Graphormer

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

Message Passing Neural Networks for Molecule Property Prediction

FAIR Chemistry's library of machine learning methods for chemistry

A deep learning package for many-body potential energy representation and molecular dynamics

The official sources for the RDKit library

MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Implementation of Alphafold 3 from Google Deepmind in Pytorch

AlphaFold 3 inference pipeline.