Proto is not affiliated with Scripps Research and the Forli Lab. This toolkit is open source and builds on the implementations produced by these organizations. Product names, logos, and trademarks are the property of their respective owners.

```bibtex theme={null} @article{eberhardt2021autodockvina, title={{AutoDock Vina 1.2.0}: New Docking Methods, Expanded Force Field, and Python Bindings}, author={Eberhardt, Jerome and Santos-Martins, Diogo and Tillack, Andreas F. and Forli, Stefano}, journal={Journal of Chemical Information and Modeling}, volume={61}, number={8}, pages={3891--3898}, year={2021}, publisher={American Chemical Society}, doi={10.1021/acs.jcim.1c00203} } @article{trott2010autodockvina, title={{AutoDock Vina}: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading}, author={Trott, Oleg and Olson, Arthur J.}, journal={Journal of Computational Chemistry}, volume={31}, number={2}, pages={455--461}, year={2010}, publisher={Wiley}, doi={10.1002/jcc.21334} } @article{santosmartins2025meeko, title={Meeko: Molecule Parametrization and Software Interoperability for Docking and Beyond}, author={Santos-Martins, Diogo and He, Yiran and Eberhardt, Jerome and Sharma, Parnika and Bruciaferri, Niccolo and Holcomb, Matthew and Llanos, Manuel A. and Hansel-Harris, Althea and Barkdull, Allison Pearl and Tillack, Andreas Frank and Bianco, Giulia and Paulsen, May-Linn and Mato, Joani and Taneja, Ishan and Forli, Stefano}, journal={Journal of Chemical Information and Modeling}, volume={65}, number={24}, pages={13045--13050}, year={2025}, publisher={American Chemical Society}, doi={10.1021/acs.jcim.5c02271} } @article{quiroga2016vinardo, title={Vinardo: A Scoring Function Based on {AutoDock Vina} Improves Scoring, Docking, and Virtual Screening}, author={Quiroga, Rodrigo and Villarreal, Marcos A.}, journal={PLOS ONE}, volume={11}, number={5}, pages={e0155183}, year={2016}, publisher={Public Library of Science}, doi={10.1371/journal.pone.0155183} } @article{nagar2002abl, title={Crystal Structures of the Kinase Domain of {c-Abl} in Complex with the Small Molecule Inhibitors {PD173955} and Imatinib ({STI-571})}, author={Nagar, Bhushan and Bornmann, William G. and Pellicena, Patricia and Schindler, Thomas and Veach, Darren R. and Miller, W. Todd and Clarkson, Bayard and Kuriyan, John}, journal={Cancer Research}, volume={62}, number={15}, pages={4236--4243}, year={2002}, publisher={American Association for Cancer Research}, pmid={12154025}, url={https://pubmed.ncbi.nlm.nih.gov/12154025/} } ```

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### AutoDock Vina Docking (`vina-docking`) Prepares one rigid receptor and one or more small-molecule ligands, searches either an explicit box or a box derived from a coordinate-bearing reference ligand, and returns the ranked poses retained by Vina for each ligand. Bare SMILES strings are accepted, and a single ligand is normalized into a one-element list; the tool generates a seeded three-dimensional conformer per ligand before docking. #### API Reference

Source Receptor coordinates to parameterize as a rigid PDBQT model. Raw structure content in PDB or CIF format. Format of the content string (auto-detected if omitted). What the B-factor column represents. Optional source identifier (filepath or tool name). Associated metrics (e.g., pLDDT, pTM scores, per-chain lists, pairwise matrices). None values are stripped at construction. Small molecules to dock against the receptor, each scored independently. SMILES strings are accepted, and a single ligand is normalized into a one-element list. Optional identifier (free-form; e.g. a chain letter for in-complex use). SMILES string (canonicalized to RDKit form on construction). CCD code from the Chemical Component Dictionary. Always `"ligand"`. Lets Fragments be used interchangeably with `Chain` in structure-prediction inputs. Human-readable molecule name. Computed metrics for this fragment. Explicit search box or a box derived from a reference ligand in the receptor coordinate frame.

Source Vina-family scoring function. Available options: `vina`, `vinardo` Number of independent Monte Carlo search runs. Maximum poses retained and returned. Maximum affinity difference from the best returned pose. Minimum RMSD separation between retained poses. Search evaluation cap; zero uses Vina's heuristic. Worker threads; zero lets Vina use all available CPUs. Affinity-map grid spacing in angstroms. Delete receptor residues Meeko cannot parameterize. Verbosity level (0=quiet, 1=info, 2=debug, 3=raw subprocess stderr). `True` is coerced to `1` and `False` to `0`. Device to run the tool on. Maximum execution time in seconds. `None` waits indefinitely. Positive signed 32-bit seed; generated and returned when omitted.

Source One entry per input ligand, in input order. SMILES of the docked ligand, echoed for provenance. Seed actually used for this ligand, advanced from the request seed by the ligand's position so duplicate ligands still sample independently. Ranked poses in ascending affinity order. This ligand's returned poses in a combined SDF payload. This ligand's returned poses in a combined PDBQT payload. Force field used to minimize the input conformer. Whether conformer minimization converged. Conformer minimization attempts made. Iteration cap used for each attempt. Ligand-specific preparation warnings. Concrete random seed used by Vina and ligand conformer generation. Resolved search-box coordinates. Use an explicitly positioned search box. Box center `(x, y, z)` in angstroms. Positive box dimensions `(x, y, z)` in angstroms. Scoring function used. **Metrics** (one set per `results` item) | Metric | Type | Range | Availability | | ------------------ | ----- | --------- | ------------ | | `affinity` | float | unbounded | always | | `rmsd_lower_bound` | float | ≥ 0.0 | always | | `rmsd_upper_bound` | float | ≥ 0.0 | always |

#### Applications Use this tool for redocking a known ligand into an experimental receptor, proposing binding modes for analogs, screening a focused set of compounds against a defined pocket, or producing initial protein-ligand poses for molecular dynamics and free-energy workflows. It is also useful for checking whether a designed pocket can accommodate a candidate ligand without severe steric conflicts. #### 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.