IDENTIFICATION OF NOVEL SARS-COV-2 ENTRY INHIBITORS VIA STRUCTURE BASED HIERARCHICAL VIRTUAL

Abstract

A novel coronavirus (2019-nCov) is a pneumatic infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has declared pandemic by the World Health Organization (WHO). However, there is no efficient drug therapy available to combat with this deadliest disease. By considering the public-health emergency, most of the SARS CoV inhibitors and antiviral drugs are utilized for the treatment of COVID-19 infection. Herein, we presented integrated drug design strategies using E-pharmacophore modeling, molecular docking and molecular dynamic simulation studies based on the recently published SARS-CoV-2 RBD protein structure. Structure-based pharmacophore model (ADHRR) and high-throughput virtual screening (HTVS) were used to screen ZINC and ChEMBL molecular databases for identifying novel SARS-CoV-2 entry inhibitors. The retrieved potential hits were taken for the comparative molecular docking against SARSCoV-2 and SARS-CoV enzymes to understand the different binding interactions. Further, the stability of receptor-ligand complex and specific amino acid interactions was evaluated by performing molecular dynamic simulation of 30 ns in solvated model system. This study identified ZINC00662497, ZINC00669387, ZINC08426008, ZINC0660155 and ZINC0844005 as promising leads for inhibiting the entry of 2019-nCoV virus.