Structure Based Drug Design Approach to Identify Potential SARS-CoV-2 Polymerase Inhibitors

Abstract

Aims: The research work aims to apply the current virtual screening approaches for rapid screening of available compounds as inhibitors of the novel coronavirus (COVID-19). Background: The worldwide pandemic, uncontrolled spread, and lack of effective therapeutics demand novel SARS-CoV-2 inhibitory anti-viral agents. Objective: The major objectives of the present work are – i) effective utilization of open-source computer- aided drug design (CADD) tools; ii) to prepare a database according to chemical structure similarity to the reported anti-viral drug, Favipiravir; and iii) to investigate potential inhibitors of the novel coronavirus. Methods: The dataset was prepared based on the chemical structure similarity feature of ChemSpider. The virtual screening was carried out using molecular docking and ADMET properties. For performing molecular docking studies, the standard docking protocol of iGEMDOCK was used. Result: Based on chemical structure similarity search to Favipiravir, a small library of 40 compounds was designed. The docking score and ADMET properties were analyzed to prioritize the compounds. Conclusion: The virtual screening resulted in the identification of potential anti-viral compounds. Among the designed library of compounds based on structural similarity to Favipiravir, 70% of compounds were found to possess docking scores more than that of Favipiravir. The amino acid residues involved in binding at the RNA dependent RNA polymerase (RdRp) were identified. The compounds have shown acceptable ADME properties and are potentially non-toxic. Other: The study has successfully applied the open source CADD tools to investigate novel SARS-CoV-2 polymerase inhibitors.