Computational investigation of honeybee venom proteins as potential Omicron SARS-CoV-2 inhibitors

Abstract

Because of the catastrophic consequences of COVID-19 on the world population, there should be novel­ interventions to handle ongoing infections and daily death cases. The aim of the current study is to examine the effectiveness of HBV (Honeybee venom) proteins on spike protein RBD by in silico tools. The sequences of 5 HBV proteins were used for homology modeling by Phyre 2. The generated protein models were employed for protein-protein docking against Omicron Spike glycoprotein receptor binding domain (RBD) (PDB ID# 7T9L) through HDock and ClusPro platforms followed by prediction of binding affinity using PRODIGY web portal and PDBsum for revealing interaction details. It was found that all of the examined HBV proteins exhibi­ted strong docking scores and binding affinity profiles toward RBD. The findings of the present study indicate the possible HBV as preventive as well as treatment options against Omicron SARS-CoV-2. Keywords: COVID-19, docking, Honeybee venom, RBD, SARS-COV-2