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

Author:

Tahir Rana Adnan1ORCID,Mughal Sumera2,Nazir Amina3,Noureen Asma4,Jawad Ayesha2,Waqas Muhammad5,Sehgal Sheikh Arslan6ORCID

Affiliation:

1. Department of Biosciences, COMSATS University Islamabad, Sahiwal Campus,Pakistan | Key Laboratory of Molecular Medicine and Biotherapy in the Ministry of Industry and Information Technology, Department of Biology, School of Life Sciences, Beijing Institute of Technology, Beijing, China

2. Department of Biosciences, COMSATS University Islamabad, Sahiwal Campus,Pakistan

3. Key Laboratory of Molecular Medicine and Biotherapy in the Ministry of Industry and Information Technology, Department of Biology, School of Life Sciences, Beijing Institute of Technology, Beijing,China

4. Department of Zoology, Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan

5. Department of Bioinformatics and Biotechnology, Government College University Faisalabad,Pakistan

6. Department of Bioinformatics, University of Okara, Okara,Pakistan

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 life cycle and nonstructural proteins of HCV involved in viral replication are the attractive targets for the development of antiviral drugs. Methods: In this work, pharmacoinformatics approaches coupled with docking analyses were applied on HCV nonstructural proteins to identify the novel potential hits and HCV drugs. Molecular docking analyses were carried out on HCV approved drugs followed by the ligand-based pharmacophore generation to screen the antiviral libraries for novel potential hits. Results: Virtual screening technique has made known the top-ranked five novel compounds (ZINC00607900, ZINC03635748, ZINC03875543, ZINC04097464, and ZINC12503102) along with the least binding energy (-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 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.

Publisher

Bentham Science Publishers Ltd.

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine

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