entity-complex

pythonic interface to virtual screening software

AutoDock Vina

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.

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

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

Predicting protein-ligand binding sites using deep convolutional neural network

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

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

A comprehensive macromolecular library

This package contains deep learning models and related scripts for RoseTTAFold

An open library to work with pharmacophores.

MD pharmacophores and virtual screening

Open-source foundation of the user-sponsored PyMOL molecular visualization system.

Interface for AutoDock, molecule parameterization

Open source code for AlphaFold 2.

Protein Ligand INteraction Dataset and Evaluation Resource

Identification of Protein-Ligand Binding Sites using dipolar EPR data

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

📐 Symmetry-corrected RMSD in Python