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.
Codes for our paper "Programming Biomolecular Interactions with All-Atom Generative Model"
Adds or removes hydrogen atoms to achieve the appropriate molecular protonation state for a user-specified pH range
Python3 translation of AutoDockTools
Biomolecular simulation trajectory/data analysis.
Parameter/topology editor and molecular simulator
Official Github for "PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening" (Chemical Science)
Open-Source Quantum Chemistry – an electronic structure package in C++ driven by Python
Identification of Protein-Ligand Binding Sites using dipolar EPR data
Semiempirical Extended Tight-Binding Program Package
Library for computing dynamic non-covalent contact networks in proteins throughout MD Simulation
Deep Site and Docking Pose (DSDP) is a blind docking strategy accelerated by GPUs, developed by Gao Group. For the site prediction part, several modifications are introduced to PUResNet program. The pose sampling part is similar as AutoDock Vina combined with a number of modifications.
Calculation of interatomic interactions in molecular structures
A deep learning framework for molecular docking
A pocket volume analyzer for use in protein modeling.
Predicting protein-ligand binding sites using deep convolutional neural network
The second version of the Kraken taxonomic sequence classification system
Prediction of binding residues for metal ions, nucleic acids, and small molecules.
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