Medicinal plant compounds as promising inhibitors of coronavirus (COVID-19) main protease: an in silico study

Abstract

The novel Coronavirus (COVID-19) has spread rapidly across the globe and has involved more than 215 countries and territories. Due to a lack of effective therapy or vaccine, urgent and concerted efforts are needed to identify therapeutic targets and medications. COVID-19 main protease represents a major target for drug treatment to inhibit viral function. The present study sought to evaluate medicinal plant compounds as potential inhibitors of the COVID-19 main protease using molecular docking and molecular dynamic analysis. The PDB files of COVID-19 main protease and some medicinal plant compounds were retrieved from the Protein Data Bank (http://www.rcsb.org) and Pubchem server, respectively. The Gromacs software was used for simulation studies, and molecular docking analysis was done using Autodock 4.2. The COVID-19 main protease simulation, compared with some phytochemicals docked to the COVID-19 main protease, were analyzed. Glabridin, catechin, and fisetin had the greatest tendency to interact with the COVID-19 main protease by hydrogen and hydrophobic interactions. Docking of these phytochemicals to COVID-19 main protease led to an increase in the radius of gyration (Rg), decrease in the Root mean square fluctuation (RMSF), and induced variation in COVID-19 main protease secondary structure. The high tendency interaction of glabridin, catechin, and fisetin to COVID-19 main protease induced conformational changes on this enzyme. These interactions can lead to enzyme inhibition. This simulated study indicates that these phytochemicals may be considered as potent inhibitors of the viral protease; however, more investigations are required to explore their potential medicinal use.

Communicated by Ramaswamy H. Sarma

Keywords:

• COVID-19 main protease
• medicinal plant compounds
• inhibitors
• molecular docking

Disclosure statement

The authors declare no conflicts of interest.

This study was based on a research project (no: 3279) funded by the Deputy of Research and Technology of Shahrekord University of Medical Sciences, Shahrekord, Iran. We gratefully thank this deputy.