State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

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

Message Passing Neural Networks for Molecule Property Prediction

A powerful and flexible machine learning platform for drug discovery

Protein Graph Library

Therapeutics Commons: Artificial Intelligence Foundation for Therapeutic Science

A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)

Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

Python package for graph neural networks in chemistry and biology

Working with molecular structures in pandas DataFrames

OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research

A deep learning framework for molecular docking

NequIP is a code for building E(3)-equivariant interatomic potentials

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models

Molecular Processing Made Easy.

Deep Reinforcement Learning for de-novo Drug Design

Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials

HTMD: Programming Environment for Molecular Discovery