molclaw-diffdock-auto

You can automate protein-ligand docking by providing batch CSV inputs to run DiffDock inference, returning per-complex confidence summaries and output files for scalable prioritization.

DiffDock docking automation accepts protein PDB files, ligand SMILES strings, and batch CSV files as valid inputs to execute single or multiple docking workflows for drug discovery evaluation.

Yes, you can use the optional dry_run mode to validate protein PDB and ligand inputs without executing the full docking inference, ensuring safe execution and returning clear status metadata for downstream pipelines.

DiffDock confidence summaries provide per-complex scoring that guides drug discovery prioritization and decision making, allowing you to evaluate and rank scalable batch docking results effectively for downstream analysis.

DiffDock automation supports reproducibility by providing downloadable output files and results metadata, ensuring local file uploads are safely handled and exported for downstream pipeline integration.