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

A comprehensive macromolecular library

Predicting protein-ligand binding sites using deep convolutional neural network

Codes for our paper "Programming Biomolecular Interactions with All-Atom Generative Model"

Comprehensive library for fast, GPU accelerated molecular gridding for deep learning workflows

Predict protein-ligand and catalytic pockets and perform molecular docking of a specific ligand to each predicted pocket.

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.

pythonic interface to virtual screening software

Official Github for "PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening" (Chemical Science)

AutoDock Vina

Identification of Protein-Ligand Binding Sites using dipolar EPR data

Library for computing dynamic non-covalent contact networks in proteins throughout MD Simulation

Experiments with expanded ensembles to explore chemical space

A versatile workflow for the generation of receptor-based pharmacophore models for virtual screening

MD pharmacophores and virtual screening

This package contains deep learning models and related scripts for RoseTTAFold

An open library to work with pharmacophores.

📐 Symmetry-corrected RMSD in Python

A Euclidean diffusion model for structure-based drug design.

Interface for AutoDock, molecule parameterization