A comprehensive macromolecular library
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Updated
Jul 29, 2026 - TypeScript
A comprehensive macromolecular library
pythonic interface to virtual screening software
Predicting protein-ligand binding sites using deep convolutional neural network
Official Github for "PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening" (Chemical Science)
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
Codes for our paper "Programming Biomolecular Interactions with All-Atom Generative Model"
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.
Predict protein-ligand and catalytic pockets and perform molecular docking of a specific ligand to each predicted pocket.
An open library to work with pharmacophores.
This package contains deep learning models and related scripts for RoseTTAFold
Identification of Protein-Ligand Binding Sites using dipolar EPR data
Library for computing dynamic non-covalent contact networks in proteins throughout MD Simulation
Open-source foundation of the user-sponsored PyMOL molecular visualization system.
Interface for AutoDock, molecule parameterization
A Euclidean diffusion model for structure-based drug design.
📐 Symmetry-corrected RMSD in Python
MD pharmacophores and virtual screening
Experiments with expanded ensembles to explore chemical space
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