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)

Author:

Brogi SimoneORCID,Rossi SaraORCID,Ibba RobertaORCID,Butini StefaniaORCID,Calderone Vincenzo,Campiani Giuseppe,Gemma SandraORCID

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.

Funder

Fondo di Beneficenza di Intesa Sanpaolo

Publisher

MDPI AG

Subject

Applied Mathematics,Modeling and Simulation,General Computer Science,Theoretical Computer Science

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