A Combined approach of QSAR study, molecular docking and pharmacokinetics prediction of promising Amide-Ac6-aminoacetonitriles Cathepsin K inhibitors

Cathepsin K (Cat-K) highly expressed in osteoclasts, is considered to be a promising target for osteoclast-related maladies. In the present study, quantitative structure-activity relationships (QSAR) and molecular docking approaches were used to identify promising Cat-K inhibitors from a series of Amide-Ac6-aminoacetonitriles analogs. During the two-dimensional QSAR study, the statistical model PLS_MDL was chosen (r(2) = 0.823, q(2) (cross-validation) = 0.732). Descriptors with positive or negative contributions were derived from model PLS_MDL. In order to build robust three-dimensional QSAR models, three different molecular fingerprints were used as analysis precepts for clustering and three different minimization algorithms were employed for generation of molecular poses. The best database which used molecular fingerprint of FCFP and minimization algorithm of Smart Minimizer was selected for further QSAR model construction. The ideal CoMFA and CoMSIA models were acquired (CoMFA: r(2) = 0.963, q(2) = 0.674, r(pred)(2) = 0.702 and Q((F2))(2) = 0.616; CoMSIA_SEHA: r(2) = 0.989, q(2) = 0.622, r(pred)(2) = 0.719 and Q((F2))(2) = 0.638). Physicochemical, structural, electrostatic, and steric properties were derived from the created QSAR models and then applied to portray a design scheme. Furthermore, after a selecting of docking scheme, docking studies were carried out to measure the binding affinity of eligible query compounds and to reveal the detailed interactions between ligand and the target protein. Amongst these designed compounds, compound 19OX32 was focused for its preferable predicted activity and docking score. Strong interactions and extra hydrogen bonds which echoed the previous summarized design scheme were also observed via a deep investigation of docking result. Consequently, compound 19OX32 was identified as promising Cat-K inhibitor. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

In this study, a promising Cat-K inhibitor was identified from a series of compounds using QSAR and molecular docking approaches. Robust three-dimensional QSAR models were built using different molecular fingerprints and minimization algorithms, leading to the discovery of ideal CoMFA and CoMSIA models. Compound 19OX32 was identified as a promising Cat-K inhibitor due to its predicted activity and docking score.