Computational drug repurposing study of antiviral drugs against main protease, RNA polymerase, and spike proteins of SARS-CoV-2 using molecular docking method

Abstract

Abstract Objectives The new Coronavirus (SARS-CoV-2) created a pandemic in the world in late 2019 and early 2020. Unfortunately, despite the increasing prevalence of the disease, there is no effective drug for the treatment. A computational drug repurposing study would be an appropriate and rapid way to provide an effective drug in the treatment of the coronavirus disease of 2019 (COVID-19) pandemic. In this study, the inhibitory potential of more than 50 antiviral drugs on three important proteins of SARS-CoV-2, was investigated using the molecular docking method. Methods By literature review, three important proteins, including main protease, RNA-dependent RNA polymerase (RdRp), and spike, were selected as the drug targets. The three-dimensional (3D) structure of protease, spike, and RdRp proteins was obtained from the Protein Data Bank. Proteins were energy minimized. More than 50 antiviral drugs were considered as candidates for protein inhibition, and their 3D structure was obtained from Drug Bank. Molecular docking settings were defined using Autodock 4.2 software and the algorithm was executed. Results Based on the estimated binding energy of docking and hydrogen bond analysis and the position of drug binding, five drugs including, indinavir, lopinavir, saquinavir, nelfinavir, and remdesivir, had the highest inhibitory potential for all three proteins. Conclusions According to the results, among the mentioned drugs, saquinavir and lopinavir showed the highest inhibitory potential for all three proteins compared to the other drugs. This study suggests that saquinavir and lopinavir could be included in the laboratory phase studies as a two-drug treatment for SARS-CoV-2 inhibition.