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Combinatorial Chemistry & High Throughput Screening

Editor-in-Chief

ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Research Article

The Life Cycle and in silico Elucidation of Non-structural Replicating Proteins of HCV Through a Pharmacoinformatics Approach

Author(s): Rana Adnan Tahir, Sumera Mughal, Amina Nazir, Asma Noureen, Ayesha Jawad, Muhammad Waqas and Sheikh Arslan Sehgal*

Volume 25, Issue 4, 2022

Published on: 17 February, 2021

Page: [689 - 701] Pages: 13

DOI: 10.2174/1386207324666210217144306

Price: $65

Abstract

Background: Hepatitis C virus (HCV) is an enveloped and positive-stranded RNA virus that is a major causative agent of chronic liver diseases worldwide. HCV has become the main cause of liver transplantations and there is no effective drug for all hepatitis genotypes. Elucidation of the life cycle and non-structural proteins of HCV, involved in viral replication, are attractive targets for the development of antiviral drugs..

Methods: In this work, pharmacoinformatics approaches coupled with docking analyses were applied on HCV non-structural proteins to identify the novel potential hits and HCV drugs. Molecular docking analyses were carried out on HCV-approved drugs, followed by the ligandbased pharmacophore generation to screen the antiviral libraries for novel potential hits.

Results: Virtual screening technique has top-ranked five novel compounds (ZINC00607900, ZINC03635748, ZINC03875543, ZINC04097464, and ZINC12503102) along with their least binding energies (-8.0 kcal/mol, -6.1 kcal/mol, -7.5 kcal/mol, -7.4 kcal/mol, and -7.3 kcal/mol, respectively) and stability with the non-structural proteins target.

Conclusion: These promising hits exhibited better absorption and ADMET properties as compared to the selected drug molecules. These potential compounds extracted from in silico approach may be significant in drug design and development against Hepatitis and other liver diseases.

Keywords: Hepatitis, HCV, NS proteins, pharmacoinformatics, molecular docking, HCV life cycle.

Graphical Abstract

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