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Determination of Binding Potential of HCV Protease Inhibitors Against to SARS-CoV-2 Papain-like Protease wtih Computational Docking

Authors: Zihni Onur Çalışkaner;

Determination of Binding Potential of HCV Protease Inhibitors Against to SARS-CoV-2 Papain-like Protease wtih Computational Docking

Abstract

Background: SARS-CoV-2, a novel coronavirus that caused a pandemic respiratory disease, has recently emerged from China. Since it is a life-threatening virus, investigation of curative medications along with protective vaccines still maintains its importance. Drug repurposing is a reasonable and immediate approach to combat SARS-CoV-2 infection by identifying inhibitory molecules from marketed drugs. PL protease (PLpro) is one of the essential enzymes for the progression of SARS-CoV-2 replication and life cycle. Objective: We aimed to investigate the potential of 4 HCV protease inhibitors as probable repurposing drugs in Covid-19 treatment. Methods: In order to understand possible binding affinity of HCV protease inhibitors, Boceprevir, Grazoprevir, Simeprevir, and Telaprevir, against PLpro, we performed docking analysis in silico. Docking study was accomplished using AutoDock 4.2 Software. Potential druggable pockets on PLpro were predicted by DoGSiteScorer tool in order to explore any overlapping with binding regions and these pockets. Results: This analysis demonstrated Boceprevir, Grazoprevir, Simeprevir and Telaprevir interacted by PLpro with binding energies (kcal/mol) of -4.97, -4.24, -6.98, -1.08, respectively. Asn109, one of the interacted residues with both Boceprevir and Simeprevir, is a neighbouring residue to catalytic Cys111. Additionally, Telaprevir notably interacted with catalytic His272 in the active site. Conclusion: Present study explains the binding efficiency and repurposing potential of certain HCV protease inhibitors against to SARS-CoV-2 PLpro enzyme. Docking sites and potential druggability of ligands were also crosschecked by the estimation of druggable pockets. Thereby our results can promote promising preliminary data for research on drug development in the fight of Covid-19.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average