Monte Carlo Method Based QSAR Modeling of Coumarin Derivates as Potent HIV‐1 Integrase Inhibitors and Molecular Docking Studies of Selected 4‐phenyl Hydroxycoumarins

Abstract

Summary In search for new and promising coumarin compounds as HIV-1 integrase inhibitors, chemoinformatic methods like quantitative structure-activity relationships (QSAR) modeling and molecular docking have an important role since they can predict desired activity and propose molecule binding to enzyme. The aim of this study was building of QSAR models for coumarin derivatives as HIV-1 integrase inhibitors with the application of Monte Carlo method. SMILES notation was used to represent the molecular structure and for defining optimal SMILES-based descriptors. Molecular docking into rigid enzyme active site with flexible molecule was performed. Computational results indicated that this approach can satisfactorily predict the desired activity with very good statistical significance. For best built model statistical parameters were: a) 3’ Processing activity: R2=0.9980 and Q2=0.9977 for training set and R2=0.9788 for test set and b) Integration activity: R2=0.9999 and Q2=0.9998 for training set and R2= 0.9213 for test set. Built QSAR models were applied to selected 4-phenyl hydroxycoumarins for calculating desired activity and for HIV-1 integrase inhibition estimation. Additionally, molecular docking study was performed to a newly identified pocket in the HIV-1 integrase enzyme structure for determination of selected 4-phenyl hydroxycoumarins binding mode. Monte Carlo method proved to be an efficient approach to build up a robust model for estimating HIV-1 integrase inhibition of coumarin compounds. Based on QSAR and molecular docking studies, 4-phenyl hydroxycoumarins can be considered as promising model compounds for developing new HIV-1 integrase inhibitors.