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.
Parameter/topology editor and molecular simulator
Biomolecular simulation trajectory/data analysis.
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
Codes for our paper "Programming Biomolecular Interactions with All-Atom Generative Model"
This package contains deep learning models and related scripts for RoseTTAFold
Quantum chemistry program executor and IO standardizer (QCSchema).
Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design [ICLR 2025 oral]
Semiempirical Extended Tight-Binding Program Package
Identification of Protein-Ligand Binding Sites using dipolar EPR data
Library for computing dynamic non-covalent contact networks in proteins throughout MD Simulation
Adds or removes hydrogen atoms to achieve the appropriate molecular protonation state for a user-specified pH range
Python3 translation of AutoDockTools
Raku package that interfaces Woxi (limited functionality of Wolfram Language in Rust).
Predicting protein-ligand binding sites using deep convolutional neural network
A pocket volume analyzer for use in protein modeling.
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.
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