Computational design of medicinal compounds to inhibit RBD-hACE2 interaction in the Omicron variant: unveiling a vulnerable target site

Abstract

The COVID-19 pandemic, caused by SARS-CoV-2, has globally affected both human health and economy. Several variants with a high potential for reinfection and the ability to evade immunity were detected shortly after the initial reported case of COVID-19. A total of 30 mutations in the spike protein (S) have been reported in the SARS-CoV-2 (BA.2) variant in India and South Africa, while half of these mutations are in the receptor-binding domain and have spread rapidly throughout the world. Drug repurposing offers potential advantages over the discovery of novel drugs, and one is that it can be delivered quickly without lengthy assessments and time-consuming clinical trials. In this study, computational drug design, such as pharmacophore-based virtual screening and MD simulation has been concentrated, in order to find a novel small molecular inhibitor that prevents hACE2 from binding to the receptor binding domain (RBD). three medicinal compound databases: North-East African, North African, and East African were screened and carried out a multi-step screening approach that identified three compounds, which are thymoquinol 2-O-beta-glucopyranoside (C1), lanneaflavonol (C2), and naringenin-4′-methoxy-7-O-Alpha-L-rhamnoside (C3), with excellent anti-viral properties against the RBD of the omicron variant. Furthermore, PAIN assay interference, computation bioactivity prediction, binding free energy, and dissociation constant were used to validate the top hits, which indicated good antiviral activity. The three compounds that were found may be useful against COVID-19, though more research is required. These findings could aid the development of novel therapeutic drugs against the emerging Omicron variant of SARS-CoV-2.

Keywords

• SARS-CoV-2
• hACE2
• BA.2
• Virtual screening
• MD simulation
• RBD