Assessing the Performance of Docking, FEP, and MM/GBSA Methods on a Series of KLK6 Inhibitors

Abstract

Kallikrein 6 (KLK6) is an attractive drug target for the treatment of neurological diseases and for various cancers. Herein, we explore the accuracy and efficiency of different computational methods and protocols to predict the free energy of binding (ΔGbind) of a series of KLK6 inhibitors. We found that the performance of the methods varied strongly with the tested system. For only one of the three KLK6 datasets, the docking scores were in good agreement (R2 ≥ 0.5) with experimental values of ΔGbind. A similar result was obtained with MM/GBSA calculations based on single minimized structures. Improved binding affinity predictions were obtained with the free energy perturbation (FEP) method, with an overall MUE and RMSE of 0.53 and 0.68 kcal/mol, respectively. This result indicates that FEP can be a promising tool for the structure-based optimization of KLK6 inhibitors.