facebookresearch/fairchem

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

Message Passing Neural Networks for Molecule Property Prediction

The official sources for the RDKit library

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

Graphormer is a general-purpose deep learning backbone for molecular modeling.

A curated list of awesome AI tools, libraries, papers, datasets, and frameworks that accelerate scientific discovery — from physics and chemistry to biology, materials, and beyond.

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

Practical Cheminformatics Tutorials

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