Cryptic binding pocket discovery from conformational ensembles. Open-source, reproducible, size-robust benchmarks against fpocket, PocketMiner and CryptoBench.
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Updated
Jul 23, 2026 - Python
Cryptic binding pocket discovery from conformational ensembles. Open-source, reproducible, size-robust benchmarks against fpocket, PocketMiner and CryptoBench.
A Molecular Topography MultiToolkit designed to simplify and streamline the detection, analysis, and characterization of protein pockets, cavities, channels, and binding sites.
Identification of Protein-Ligand Binding Sites using dipolar EPR data
Library for computing dynamic non-covalent contact networks in proteins throughout MD Simulation
A dependency-free cross-platform swiss army knife for PDB files.
Reduce - tool for adding and correcting hydrogens in PDB files
A comprehensive library for computational molecular biology
EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein
Official Github for "PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening" (Chemical Science)
Molsystem provides a general class for handling molecular and periodic systems
Codes for our paper "Programming Biomolecular Interactions with All-Atom Generative Model"
MoleculeKit: Your favorite molecule manipulation kit
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.
This package contains deep learning models and related scripts for RoseTTAFold
An open library to work with pharmacophores.
Consensus pharmacophore for Drug Design
fpocket is a very fast open source protein pocket detection algorithm based on Voronoi tessellation. The platform is suited for the scientific community willing to develop new scoring functions and extract pocket descriptors on a large scale level. fpocket is distributed as free open source software.
🏗️ Statistical models for biomolecular dynamics 🏗️
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