Literature DB >> 28164720

Applications of computer-aided approaches in the development of hepatitis C antiviral agents.

Aravindhan Ganesan1, Khaled Barakat1.   

Abstract

INTRODUCTION: Hepatitis C virus (HCV) is a global health problem that causes several chronic life-threatening liver diseases. The numbers of people affected by HCV are rising annually. Since 2011, the FDA has approved several anti-HCV drugs; while many other promising HCV drugs are currently in late clinical trials. Areas covered: This review discusses the applications of different computational approaches in HCV drug design. Expert opinion: Molecular docking and virtual screening approaches have emerged as a low-cost tool to screen large databases and identify potential small-molecule hits against HCV targets. Ligand-based approaches are useful for filtering-out compounds with rich physicochemical properties to inhibit HCV targets. Molecular dynamics (MD) remains a useful tool in optimizing the ligand-protein complexes and understand the ligand binding modes and drug resistance mechanisms in HCV. Despite their varied roles, the application of in-silico approaches in HCV drug design is still in its infancy. A more mature application should aim at modelling the whole HCV replicon in its active form and help to identify new effective druggable sites within the replicon system. With more technological advancements, the roles of computer-aided methods are only going to increase several folds in the development of next-generation HCV drugs.

Entities:  

Keywords:  Molecular dynamics; QSAR; binding free energy; computer-aided drug design; direct acting agents; drug discovery; hepatitis C virus; protein flexibility

Mesh:

Substances:

Year:  2017        PMID: 28164720     DOI: 10.1080/17460441.2017.1291628

Source DB:  PubMed          Journal:  Expert Opin Drug Discov        ISSN: 1746-0441            Impact factor:   6.098


  17 in total

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Journal:  Sci Rep       Date:  2019-05-02       Impact factor: 4.379

5.  Novel guanosine derivatives against Zika virus polymerase in silico.

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Journal:  J Med Virol       Date:  2019-08-29       Impact factor: 2.327

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Authors:  Abdo A Elfiky; Wael M Elshemey
Journal:  J Med Virol       Date:  2017-09-18       Impact factor: 2.327

7.  In Silico Exploration of Phytoconstituents From Phyllanthus emblica and Aegle marmelos as Potential Therapeutics Against SARS-CoV-2 RdRp.

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Journal:  Bioinform Biol Insights       Date:  2021-06-24

8.  Development of Machine Learning Models and the Discovery of a New Antiviral Compound against Yellow Fever Virus.

Authors:  Victor O Gawriljuk; Daniel H Foil; Ana C Puhl; Kimberley M Zorn; Thomas R Lane; Olga Riabova; Vadim Makarov; Andre S Godoy; Glaucius Oliva; Sean Ekins
Journal:  J Chem Inf Model       Date:  2021-07-21       Impact factor: 6.162

9.  Pharmacophore-Based Virtual Screening Toward the Discovery of Novel Anti-echinococcal Compounds.

Authors:  Congshan Liu; Jianhai Yin; Jiaqing Yao; Zhijian Xu; Yi Tao; Haobing Zhang
Journal:  Front Cell Infect Microbiol       Date:  2020-03-20       Impact factor: 5.293

10.  Ribavirin, Remdesivir, Sofosbuvir, Galidesivir, and Tenofovir against SARS-CoV-2 RNA dependent RNA polymerase (RdRp): A molecular docking study.

Authors:  Abdo A Elfiky
Journal:  Life Sci       Date:  2020-03-25       Impact factor: 5.037

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