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Research Articles

PheroxyPyrabenz and Carbopyrropyridin against major proteins of SARS CoV-2: a comprehensive in-silico molecular docking and dynamics simulation studies

ORCID Icon, , , , , , , & show all
Pages 9121-9133 | Received 08 Aug 2022, Accepted 19 Oct 2022, Published online: 01 Nov 2022
 

Abstract

The pandemic that started in 2020 left us with so much information about viruses and respiratory diseases, and the cause behind it was severe acute respiratory syndrome coronavirus-2 (SARS CoV-2). The world is still recovering, which costs so many economic and other indirect disasters; despite that, no medications are available on the market. Although the WHO approved a few vaccines on an emergency basis, the remarks and the reinfection chances are still under investigation, and a few pharmaceutical companies are also claiming that a few medications can be effective. However, there is no situation in control. SARS CoV-2 mutates and comes in different forms, making the situation unpredictable. In this study, we have screened the complete Asinex’s BioDesign library, which contains 170,269 compounds, and shorted the data against the docking score that helps in the identification of 4-[5-(3-Ethoxy-4-hydroxyphenyl)-1-(2-hydroxyethyl)-1H-pyrazol-3-yl]-1, 2-benzenediol (PheroxyPyrabenz) and 1-[(3R,4R)-1-(5-Aminopentanoyl)-4-hydroxy-3-pyrrolidinyl]-1H-pyrrolo[2,3-b]pyridine-4-carboxamide (Carbopyrropyridin) as a significant drug candidate that can work against the multiple proteins of the SARS CoV-2 resulting in seizing the complete biological process of the virus. Further, the study extended to Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and molecular dynamics (MD) simulation of both the compounds with their complexity. The complete workflow of the study has shown satisfactory results, and both drug candidates can potentially stop the hunt for drugs against this virus after its experimental validation. Further, we checked both compounds’ absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, showing case-proof validatory results.

Communicated by Ramaswamy H. Sarma

Disclosure statement

The authors declare no competing or conflict of interest.

Ethical responsibilities

This article is based on computational concepts, and the research does not physically involve any living organism or humans, so the ethical issues are not applicable.

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Availability of data and material

All the data and supplementary material can be made public after publication.

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