Pairwise Performance Comparison of Docking Scoring Functions: Computational Approach Using InterCriteria Analysis

Scoring functions are key elements in docking protocols as they approximate the binding affinity of a ligand (usually a small bioactive molecule) by calculating its interaction energy with a biomacromolecule (usually a protein). In this study, we present a pairwise comparison of scoring functions applying a multi-criterion decision-making approach based on InterCriteria analysis (ICrA). As criteria, the five scoring functions implemented in MOE (Molecular Operating Environment) software were selected, and their performance on a set of protein-ligand complexes from the PDBbind database was compared. The following docking outputs were used: the best docking score, the lowest root mean square deviation (RMSD) between the predicted poses and the co-crystallized ligand, the RMSD between the best docking score pose and the co-crystallized ligand, and the docking score of the pose with the lowest RMSD to the co-crystallized ligand. The impact of ICrA thresholds on the relations between the scoring functions was investigated. A correlation analysis was also performed and juxtaposed with the ICrA. Our results reveal the lowest RMSD as the best-performing docking output and two scoring functions (Alpha HB and London dG) as having the highest comparability. The proposed approach can be applied to any other scoring functions and protein-ligand complexes of interest.