We assessed Autoparty's hit identification efficiency in a structure-based virtual screening campaign at Pfizer. The Pfizer team screened an internal library against a protein binding site using Glide. They uploaded 4,792 compounds to Autoparty, pre-filtered based on a docking score cutoff of -6.5 and a strain energy cutoff of 5 kcal/mol. The team leveraged an unpublished ligand-protein complex to prioritize binding site pharmacophore features, specifically hydrophobic and hydrogen bond interactions with the protein. Annotators assigned grade A to docked compounds satisfying the most favorable pharmacophore features and grades from B through D to those with weaker interactions. Grade F denoted docked compounds exhibiting illogical interactions (e.g., a nonpolar group occupying a polar/charged region). A total of 72 compounds were annotated, and the predicted grades for all the compounds are illustrated in Fig.