Geometric filters for protein-ligand complexes based on phenomenological molecular models

Abstract

Molecular docking is a widely used method of computer-aided drug design capable of accurate prediction of protein-ligand complex conformations. However, scoring functions used to estimate free energy of binding still lack accuracy. Aim. Development of computationally simple and rapid algorithms for ranking ligands based on docking results. Methods. Computational filters utilizing geometry of protein-ligand complex were designed. Efficiency of the filters was verified in a cross-docking study with QXP/Flo software using crystal structures of human serine proteases thrombin (F2) and factor Xa (F10) and two corresponding sets of known selective inhibitors. Results. Evaluation of filtering results in terms of ROC curves with varying filter threshold value has shown their efficiency. However, none of the filters outperformed QXP/Flo built-in scoring function Pi . Nevertheless, usage of the filters with optimized set of thresholds in combination with Pi achieved significant improvement in performance of ligand selection when compared to usage of Pi alone. Conclusions. The proposed geometric filters can be used as a complementary to traditional scoring functions in order to optimize ligand search performance and decrease usage of computational and human resources.