Homology modeling, virtual screening, molecular docking, molecular dynamic (MD) simulation, and ADMET approaches for identification of natural anti-Parkinson agents targeting MAO-B protein

Abstract

Monoamine oxidase-B (MAO-B) is a flavin-dependent enzyme involved in various neurodegenerative disorders. Here, a dataset of 142 chalcone derivatives, collected from various natural plants, was screened by combining structure-based virtual screening and ADMET approaches. The goal is to discover novel natural chalcones as potential MAO-B inhibitors. With the help of the Gaussian 09.5 software, the 3D chemical structures of compounds were optimized using the DFT method. The 3D structure of the hMAO-B enzyme was built using the Modeller software. The optimized structures were subjected to virtual screening by Autodock Vina, implicated in PyRx software. Among the 142 natural substances, 43 were selected based on their binding affinity. Then, the pharmacokinetic proprieties and toxicity of these compounds were evaluated using ADMET analysis. Ten compounds were predicted to have ADMET characteristics with no side effects. The binding modes and interactions of the top selected compounds were then evaluated using AutoDock 4.2. Compounds P60 and P81 were found to be potential inhibitors of MAO-B compared to rasagiline, safinamid, and selegiline, the reference drugs. The stability of the selected compounds was confirmed by MD simulation. Based on this finding, compounds P60 and P81 could be considered potential hMAO-B inhibitors.