entity-complex

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

A comprehensive macromolecular library

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

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

Predicting protein-ligand binding sites using deep convolutional neural network

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

AutoDock Vina

pythonic interface to virtual screening software

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

Identification of Protein-Ligand Binding Sites using dipolar EPR data

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

MD pharmacophores and virtual screening

Experiments with expanded ensembles to explore chemical space

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

A Euclidean diffusion model for structure-based drug design.

📐 Symmetry-corrected RMSD in Python

An open library to work with pharmacophores.

This package contains deep learning models and related scripts for RoseTTAFold

Open source code for AlphaFold 2.