Computational Design of a Potential Therapeutic Peptide Against Spike Protein of SARS-CoV-2

Abbas Alibakhshi, Shahrzad Ahangarzadeh, Leila Beikmohammadi, Behnoush Soltanmohammadi, Armina Alagheband Bahrami, Mohammad Mehdi Ranjbar, Elmira Mohammadi*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)337-346
Number of pages10
JournalJournal of Computational Biophysics and Chemistry
Volume20
Issue number4
DOIs
Publication statusPublished - 1 Jun 2021

Bibliographical note

Funding Information:
The project was supported by Isfahan University of Medical Sciences [grant number: 198231]. The authors would like to thank infectious Diseases and Tropical Medicine Research Center for kind supports.

Publisher Copyright:
© 2021 Journal of Computational Biophysics and Chemistry. All Rights Reserved.

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