RMeli/gnina-torch
🔥 PyTorch implementation of GNINA scoring function for molecular docking
This project helps computational chemists and drug discovery scientists evaluate how strongly a potential drug molecule (ligand) might bind to a biological target (protein). You input 3D structural data for a protein and a ligand, and it outputs calculated scores that predict binding affinity. This allows researchers to quickly prioritize promising compounds for further study in drug development.
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Use this if you need to score molecular docking poses efficiently using deep learning to predict protein-ligand binding affinities.
Not ideal if you are looking for a full molecular docking simulation tool rather than just a scoring function.
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Language
Python
License
MIT
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Last pushed
Mar 06, 2025
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