QSAR, molecular docking and molecular dynamics of 3C-like protease inhibitors

Abstract

3C- like protease is an extremely important protease involved in the multiplicative process of coronaviruses, including the deadlyMiddle East respiratory syndrome coronavirus (MERS-CoV). 3C-like protease has become a hot research topic in the field of coronavirology. For the first time, a set of ligand- and receptorbased three-dimensional quantitative structure-activity relationships (3D-QSAR) models were carried out via comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) to explore the structure-activity correlation of 43 peptidomimetic inhibitors of the 3C-like protease of the bat coronavirus HKU4 (HKU4-CoV), which belongs to the same 2c lineage as MERS-CoV and shows high sequence similarity with MERS-CoV. Based on the ligand-based alignment, an optimal CoMSIAmodel (yielded by steric, electrostatic, H-bond donor and H-bond acceptor fields) was obtained with good predictive power of Q2 = 0.522, R2ncv = 0.996 and R2pre = 0.904 (Q2: cross-validated correlation coefficient, R2ncv: non-cross-validated correlation coefficient, R2pre: predicted correlation coefficient for the test set of compounds). Molecular docking and molecular dynamics simulations were performed according to this model to further determine the interaction mechanism between ligands and the receptor. The experimental results show: (1) based on the optimal CoMSIAmodel, the 3D contour maps vividly illustrate that the molecular biological activity is influenced by the steric, electrostatic, H-bond donor and H-bond acceptor interactions of molecular groups. (2) Based on the docking analysis, hydrophobicity, crystal water, His166 andGlu169 have important roles in the ligands and receptor binding process. (3) Molecular dynamics (MD) simulations were carried out for further verification of the reliability of the docking model, and provide two new key residues, Ser24 and Gln192, which have two strong hydrogen bonds with the ligands. Some new compounds were obtained based on the modeling that are potential peptidomimetic inhibitors of 3C- like protease. These results help establish the binding mechanism between 3C- like protease and peptidomimetic inhibitors, and provide a valuable reference for future anti-MERS-CoV drug design.