Diffusion-based docking that predicts protein-ligand poses without a predefined site. Use for blind docking, when traditional docking fails, or exploring multiple binding modes. Pipeline: prep protein (PDB) and ligand (SMILES/SDF), run inference, analyze confidence-ranked poses.
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diffdock
Overview
DiffDock uses a diffusion generative model to predict protein-ligand binding poses directly from protein structure and ligand SMILES, treating docking as a generative rather than a search problem. Unlike traditional docking tools (AutoDock Vina, Glide), DiffDock does not require a predefined binding site — it samples poses across the full protein surface. It outputs a ranked set of binding poses with associated confidence scores. DiffDock excels at blind docking tasks an
[Description truncada. Veja o README completo no GitHub.]
