Computational Design of a Potential Therapeutic Peptide Against Spike Protein of Sars-Cov-2 Publisher



Alibakhshi A¹ ; Ahangarzadeh S² ; Beikmohammadi L^{3, 10} ; Soltanmohammadi B^{4, 5} ; Bahrami AA⁶ ; Ranjbar MM⁷ ; Mohammadi E^{8, 9}
Source: Journal of Computational Biophysics and Chemistry Published:2021

Abstract

SARS-CoV-2 entrance to the host cells is started by the interaction between receptor binding domain (RBD) of the spike (S) protein on the virus with the angiotensin-converting enzyme 2 (ACE2) receptor which is very important in the onset of viral infection. Interference with this interaction can be a promising way to prevent Covid-19 infection. In this study, a novel potential therapeutic peptide was designed in silico based on the key interacting amino acids of ACE2 against SARS-CoV-2 S protein. In our computational analysis, a peptide consisting of residues 19-48 of ACE2 was chosen as the wild-type peptide. Based on this peptide, six mutant peptides (Mu-P1-6) were designed and then assessed in term of interaction with S protein. The result of protein-peptide docking by HADDOCK web server and then immunological analysis by SVMTriP epitope prediction tool leads to choose Mu-P3 as the best mutant. Molecular dynamics simulations of wild-type peptide-S protein complex and Mu-P3-S protein complex, showed Mu-P3 has better interaction with S protein than wild type peptide (interaction energies -897.14 vs. -784.13 (kJ/mol)) which can be a potential therapeutic peptide for Covid-19 pandemic. © 2021 Journal of Computational Biophysics and Chemistry. All Rights Reserved.