InteractionGraphNet: a Novel and Efficient Deep Graph Representation Learning Framework for Accurate Protein-Ligand Interaction Prediction and Large-scale Structure-based Virtual Screening

Reproduction of HamNet, PhysChem and other models on small molecules

open source repository

Optimizing AlphaFold Training and Inference on GPU Clusters

The official implementation of Energy-Inspired Molecular Conformation Optimization (ICLR 2022)

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

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

Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).

Toolbox for molecular animations in Blender, powered by Geometry Nodes.

Neural relational inference for molecular dynamics simulations

A powerful and flexible machine learning platform for drug discovery

A heterogeneous OpenCL implementation of AutoDock Vina

Improving protein–ligand docking and screening accuracies by incorporating a scoring function correction term

Jupyter Dock is a set of Jupyter Notebooks for performing molecular docking protocols interactively, as well as visualizing, converting file formats and analyzing the results.

A curated list of resources for machine learning for small-molecule drug discovery

Trainable AlphaFold implementation in JAX

Open source code for TankBind. Galixir Tenchnologies

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

Trained caffe models

Code for "An adaptive graph learning method for automated molecular interactions and properties predictions".

Official implementation of 'Structure-aware Interactive Graph Neural Networks for the Prediction of Protein-Ligand Binding Affinity' (KDD 2021)

MolRep: A Deep Representation Learning Library for Molecular Property Prediction

Effective drug-target interaction prediction with mutual interaction neural network

Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation

A library for graph deep learning research