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In Silico Analysis of Peptide-Based Derivatives Containing Bifunctional Warheads Engaging Prime and Non-Prime Subsites to Covalent Binding SARS-CoV-2 Main Protease (Mpro)

Authors :
Simone Brogi
Sara Rossi
Roberta Ibba
Stefania Butini
Vincenzo Calderone
Giuseppe Campiani
Sandra Gemma
Source :
Computation, Vol 10, Iss 5, p 69 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Despite the progress of therapeutic approaches for treating COVID-19 infection, the interest in developing effective antiviral agents is still high, due to the possibility of the insurgence of viable SARS-CoV-2-resistant strains. Accordingly, in this article, we describe a computational protocol for identifying possible SARS-CoV-2 Mpro covalent inhibitors. Combining several in silico techniques, we evaluated the potential of the peptide-based scaffold with different warheads as a significant alternative to nitriles and aldehyde electrophilic groups. We rationally designed four potential inhibitors containing difluorstatone and a Michael acceptor as warheads. In silico analysis, based on molecular docking, covalent docking, molecular dynamics simulation, and FEP, indicated that the conceived compounds could act as covalent inhibitors of Mpro and that the investigated warheads can be used for designing covalent inhibitors against serine or cysteine proteases such as SARS-CoV-2 Mpro. Our work enriches the knowledge on SARS-CoV-2 Mpro, providing a novel potential strategy for its inhibition, paving the way for the development of effective antivirals.

Details

Language :
English
ISSN :
20793197
Volume :
10
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Computation
Publication Type :
Academic Journal
Accession number :
edsdoj.98dd4e8cc65645d3a988ef1cfb6de918
Document Type :
article
Full Text :
https://doi.org/10.3390/computation10050069