suneelbvs/DiffDock
Colab version of "DiffDock: : Diffusion Steps, Twists, and Turns for Molecular Docking"
This tool helps computational chemists and drug discovery researchers predict how a small molecule (ligand) binds to a protein target. You provide the 3D structures of a protein and a ligand, and it generates the most probable binding poses of the ligand within the protein's active site. This is useful for understanding molecular interactions and guiding lead optimization in drug design.
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Use this if you need to quickly run molecular docking simulations to predict ligand-protein binding poses using a state-of-the-art diffusion-based method.
Not ideal if you require advanced customization of docking parameters or need to integrate docking into a complex, high-throughput screening pipeline.
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26
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6
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Nov 12, 2022
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