Scoring functions and their evaluation methods for protein-ligand docking: recent advances and future directions

Abstract

The scoring function is one of the most important components in structure-based drug design. Despite considerable success, accurate and rapid prediction of protein-ligand interactions is still a challenge in molecular docking. In this perspective, we have reviewed three basic types of scoring functions (force-field, empirical, and knowledge-based) and the consensus scoring technique that are used for protein-ligand docking. The commonly-used assessment criteria and publicly available protein-ligand databases for performance evaluation of the scoring functions have also been presented and discussed. We end with a discussion of the challenges faced by existing scoring functions and possible future directions for developing improved scoring functions.

Figure 1:

An illustration of categories and evaluations for scoring functions in protein-ligand docking.

Figure 2:

Correlations of binding affinity predictions for 7 knowledge-based scoring functions with the PMF validation set of 77 protein-ligand complexes (all) that consists of five classes: 16 serine protease (ser), 15 metalloprotease (met), 18 L-arabinose binding protein (L-ara), 11 endothiapepsin (end), and 17 diverse protein-ligand complexes (oth). The correlation parameter here is the square of correlation coefficient (R²) rather than correlation coefficient itself (R) to maintain consistency with the original data. The correlation data for ITScore/SE, ITScore, BLEEP and SMoG2001 are taken from our previous study, and those for DrugScore^PDB and DrugScore^CSD were calculated by the DrugScore^ONLINE server (http://pc1664.pharmazie.uni-marburg.de/drugscore/).