Official Github for "PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening" (Chemical Science)
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Updated
Jul 15, 2025 - Python
Official Github for "PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening" (Chemical Science)
Predict protein-ligand and catalytic pockets and perform molecular docking of a specific ligand to each predicted pocket.
Predicting protein-ligand binding sites using deep convolutional neural network
Codes for our paper "Programming Biomolecular Interactions with All-Atom Generative Model"
A comprehensive macromolecular library
Comprehensive library for fast, GPU accelerated molecular gridding for deep learning workflows
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.
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
Experiments with expanded ensembles to explore chemical space
A versatile workflow for the generation of receptor-based pharmacophore models for virtual screening
Open-source foundation of the user-sponsored PyMOL molecular visualization system.
Interface for AutoDock, molecule parameterization
MD pharmacophores and virtual screening
An open library to work with pharmacophores.
This package contains deep learning models and related scripts for RoseTTAFold
Open source code for AlphaFold 2.
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