Incorporating specificity into optimization: evaluation of SPA using CSAR 2014 and CASF 2013 benchmarks.

Scoring functions of protein-ligand interactions are widely used in computationally docking software and structure-based drug discovery. Accurate prediction of the binding energy between the protein and the ligand is the main task of the scoring function. The accuracy of a scoring function is normally evaluated by testing it on the benchmarks of protein-ligand complexes. In this work, we report the evaluation analysis of an improved version of scoring function SPecificity and Affinity (SPA). By testing on two independent benchmarks Community Structure-Activity Resource (CSAR) 2014 and Comparative Assessment of Scoring Functions (CASF) 2013, the assessment shows that SPA is relatively more accurate than other compared scoring functions in predicting the interactions between the protein and the ligand. We conclude that the inclusion of the specificity in the optimization can effectively suppress the competitive state on the funnel-like binding energy landscape, and make SPA more accurate in identifying the "native" conformation and scoring the binding decoys. The evaluation of SPA highlights the importance of binding specificity in improving the accuracy of the scoring functions.