Identification of Potential ACE2-Derived Peptide Mimetics in SARS-CoV-2 Omicron Variant Therapeutics using Computational Approaches

Abstract

The COVID-19 pandemic has become a global health challenge because of the emergence of distinct variants. Omicron, a new variant, is recognized as a variant of concern (VOC) by the World Health Organization (WHO) because of its higher mutations and accelerated human infection. The infection rate is strongly dependent on the binding rate of the receptor binding domain (RBD) against human angiotensin converting enzyme-2 (ACE2^human) receptor. Inhibition of protein-protein (RBDs^{(SARS-CoV-2/omicron)}-ACE2^human) interaction has been already proven to inhibit viral infection. We have systematically designed ACE2^human-derived peptides and peptide mimetics that have high binding affinity toward RBD^omicron. Our peptide mutational analysis indicated the influence of canonical amino acids on the peptide binding process. Herein, efforts have been made to explore the atomistic details and events of RBDs^{(SARS-CoV-2/omicron)}-ACE2^human interactions by using molecular dynamics simulation. Our studies pave a path for developing therapeutic peptidomimetics against omicron.