Abstract
P21-activated kinase 4 (PAK4) is a serine/threonine protein kinase, which is associated with many cancer diseases, and thus being considered as a potential drug target. In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations were performed to explore the structure-activity relationship of a series of pyrropyrazole PAK4 inhibitors. The statistical parameters of comparative molecular field analysis (CoMFA, Q2 = 0.837, R2 = 0.990, and R2pred = 0.967) and comparative molecular similarity indices analysis (CoMSIA, Q2 = 0.720, R2 = 0.972, and R2pred = 0.946) were obtained from 3D-QSAR model, which exhibited good predictive ability and significant statistical reliability. The binding mode of PAK4 with its inhibitors was obtained through molecular docking study, which indicated that the residues of GLU396, LEU398, LYS350, and ASP458 were important for activity. Molecular mechanics generalized born surface area (MM-GBSA) method was performed to calculate the binding free energy, which indicated that the coulomb, lipophilic and van der Waals (vdW) interactions made major contributions to the binding affinity. Furthermore, through 100 ns MD simulations, we obtained the key amino acid residues and the types of interactions they participated in. Based on the constructed 3D-QSAR model, some novel pyrropyrazole derivatives targeting PAK4 were designed with improved predicted activities. Pharmacokinetic and toxicity predictions of the designed PAK4 inhibitors were obtained by the pkCSM, indicating these compounds had better absorption, distribution, metabolism, excretion and toxicity (ADMET) properties. Above research provided a valuable insight for developing novel and effective pyrropyrazole compounds targeting PAK4.
Graphic abstract
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The 3D-QSAR on pyrropyrazole PAK4 inhibitors was studied for the first time and the constructed 3D-QSAR model exhibited good predictive ability and significant statistical reliability.
Molecular docking and molecular dynamics simulations were performed to obtain the binding mechanism, and the binding free energy was calculated by MM-GBSA method.
Based on the CoMFA and CoMSIA models, a series of pyrropyrazole derivatives with potential better bioactivities were designed.
ADMET properties of the newly designed PAK4 inhibitors were predicted, and these inhibitors exhibited better ADMET properties.
Highlights
Communicated by Ramaswamy H. Sarma
Disclosure statement
The authors have declared no conflict of interest.