Targeting the SARS-CoV-2 Main Protease: In Silico Study Contributed to Exploring Potential Natural Compounds as Candidate Inhibitors

Author:

Ounissi Mourad1ORCID,Rachedi Fatma Zohra1

Affiliation:

1. Department of Biology, Faculty of Natural and Life Sciences, University of Ziane Achour, BP3117, Djelfa, Algeria

Abstract

The SARS-CoV-2 main protease (Mpro) is one of the essential therapeutic keys of the COVID-19, which ensures the replication of the virus in the host cells, causing tissue damage, for this reason, we accelerate the research of potential natural compounds that could inhibit this enzyme or used as a scaffold to generate a series of optimized and potent inhibitors. In silico study was performed. This study was started with the generation and validation of a structure-based pharmacophore hypothesis that is used to screen a chemical library containing 99,049 natural compounds extracted, filtered, and cleaned from the Chinese universal natural products database (UNPD), the screening process using the pharmacophore hypothesis and the molecular docking yielded 15 hits. These hits were ranked depending on their binding [Formula: see text], as a result, the two compounds UNPD90246 and UNPD221225 exhibited higher binding affinity to the catalytic cavity of the Mpro interacting with important amino acids which play a crucial role in the enzyme catalysis, on the other hand, the two complexes UNPD90246/5R82 and UNPD221225/5R82 subjected to the molecular dynamic simulation show very good stability along the trajectory of the simulation as revealed by the calculated RMSD, RMSF, rGyr, SASA as well as the RMSF of the protein and the potential energy. In addition, the in silico evaluation of some drug-like and pharmacokinetic (ADMET) properties, revealed in general satisfactory prediction results for almost all compounds, however, some compounds require optimization steps to improve their weakness, regarding pharmacokinetic properties such as metabolism and toxicity.

Publisher

World Scientific Pub Co Pte Ltd

Subject

Computational Theory and Mathematics,Physical and Theoretical Chemistry,Computer Science Applications

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