AutoDock Vina

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AutoDock Vina Docking (vina-docking)

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API Reference

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Applications

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Usage Tips

• Define the search box from pocket evidence. Use VinaSearchBox when a known pocket center is available. Use VinaReferenceLigandBox when a co-crystallized ligand is aligned to the receptor; padding is added on both sides of each ligand axis.
• Keep the box focused but large enough for the ligand. An oversized box makes the search less efficient, while a box that clips the ligand or pocket can exclude valid poses. A 20 to 25 angstrom box is a common starting point for drug-like ligands.
• Stay within the grid-allocation limits. Each box axis is limited to 100 angstroms, grid_spacing must be at least 0.1 angstrom, and the resolved map may contain at most 2,000,000 grid points. Increase spacing or reduce the box when validation reports a larger allocation.
• Prepare the receptor’s chemical state deliberately. Resolve missing atoms, alternate locations, protonation states, cofactors, metals, and waters before docking. Meeko adds missing hydrogens from its residue templates but does not perform environment-aware pKa prediction; a hydrogen-free ambiguous histidine can therefore receive the default HIE template. Inspect receptor_template_assignments in output metadata. Unsupported residues fail by default; allow_bad_residues=True deletes residues Meeko cannot parameterize, reports their identifiers in ignored_receptor_residues, and emits a warning.
• Encode ligand protonation and stereochemistry in the SMILES. The tool preserves the input graph, generates a new seeded conformer, and minimizes it with MMFF94 or UFF when parameters are available. It does not enumerate tautomers, protonation states, or undefined stereocenters; an undefined center may produce one seed-dependent geometry. Specify stereochemistry explicitly and evaluate each intended chemical state as a separate input.
• Pass a whole ligand set in one call. ligands is the per-item field, so a screen is fanned out and cached per ligand rather than per call. Receptor preparation is the expensive setup step and depends only on the receptor, so it runs once and is reused for every ligand in a request. Results are returned in input order, one entry per ligand. Each ligand advances the request seed by its position, so duplicate ligands in one call still sample independently while a given (seed, position) stays reproducible.
• visualize_search_box(inputs, config) in helpers.py draws the receptor with the resolved search box, and the reference ligand when the box was derived from one, so a misplaced or undersized box is visible before the run. Passing the config also reports the affinity-map grid size and flags an oversized grid up front rather than at dispatch.
• Increase exhaustiveness for production searches. The default of 8 is suitable for an initial run. Larger or more flexible ligands often need repeated seeds and higher exhaustiveness to establish that the top-ranked pose is stable.
• Use seed for exact reruns. When omitted, the framework generates a positive signed 32-bit seed and returns it in the output. Reuse the returned seed with the same environment and configuration to reproduce the search.
• Treat affinity as a ranking signal, not an absolute binding measurement. Compare scores only across chemically and procedurally consistent runs, and inspect interactions and pose plausibility before drawing conclusions.
• Use SDF for downstream chemistry workflows. Each pose and the combined result are returned as SDF with reconstructed bond orders. PDBQT is also retained for AutoDock interoperability and auditability.