In Silico Study Of Flavonoid Compounds: Utilization Of Computational Approach To Find Out Drug Candidate For Covid-19

Abstract

The emergence of a new human betacoronavirus strain called Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) as the causative agent of CoronaVirus Disease 19 (COVID-19) has caused a pandemic. According to previous experiments, it is known that the 3C-like protease of SARS-CoV-2 plays an important role in the pathogenicity of the virus. Flavonoids are a group of natural substances belonging to a class of plant secondary metabolites consisting of various phenolic structures and based on previous research have the ability to fight many kinds of diseases. The aim of this study is to conduct in silico studies of molecular simulation which are molecular docking and molecular dynamics to find out the best drug candidate for COVID-19 from flavonoid compounds. Screening of the potential compound was conducted through previous literature and PASS online servers. Screened compound goes into molecular docking with 3CLpro of SARS-CoV-2 and is ranked based on the binding free energy. There are 20 potential compounds that are able to bind with SARS- CoV-2 3Clpro based on the prediction from molecular docking. Visualization of the compound was done using Ligplot+ and toxicity analysis was done using SwissADME and Toxtree to assess the potential toxicity reaction. Molecular dynamics was conducted to amentoflavone and genistein which have the lowest binding free energy compared to other potential compound and it showed that the binding of the mentioned flavonoid compounds does not alter the stability of the 3CLpro structure. Based on virtual screening conducted, flavonoid compounds have the potential to bind with the 3CLpro of SARS-CoV-2.