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An in silico approach to analyze HCV genotype-specific binding-site variation and its effect on drug–protein interaction

Genotype variation in viruses can affect the response of antiviral treatment. Several studies have established approaches to determine genotype-specific variations; however, analyses to determine the effect of these variations on drug–protein interactions remain unraveled. We present an in-silico ap...

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Autores principales: Khalid, Ramsha, Anwar, Muhammad Faraz, Raees, Muhammad Aanish, Naeem, Sadaf, Abidi, Syed Hani, Ali, Syed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7705671/
https://www.ncbi.nlm.nih.gov/pubmed/33257748
http://dx.doi.org/10.1038/s41598-020-77720-9
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author Khalid, Ramsha
Anwar, Muhammad Faraz
Raees, Muhammad Aanish
Naeem, Sadaf
Abidi, Syed Hani
Ali, Syed
author_facet Khalid, Ramsha
Anwar, Muhammad Faraz
Raees, Muhammad Aanish
Naeem, Sadaf
Abidi, Syed Hani
Ali, Syed
author_sort Khalid, Ramsha
collection PubMed
description Genotype variation in viruses can affect the response of antiviral treatment. Several studies have established approaches to determine genotype-specific variations; however, analyses to determine the effect of these variations on drug–protein interactions remain unraveled. We present an in-silico approach to explore genotype-specific variations and their effect on drug–protein interaction. We have used HCV NS3 helicase and fluoroquinolones as a model for drug–protein interaction and have investigated the effect of amino acid variations in HCV NS3 of genotype 1a, 1b, 2b and 3a on NS3-fluoroquinolone interaction. We retrieved 687, 667, 101 and 248 nucleotide sequences of HCV NS3 genotypes 1a, 1b, 2b, and 3a, respectively, and translated these into amino acid sequences and used for genotype variation analysis, and also to construct 3D protein models for 2b and 3a genotypes. For 1a and 1b, crystal structures were used. Drug–protein interactions were determined using molecular docking analyses. Our results revealed that individual genotype-specific HCV NS3 showed substantial sequence heterogeneity that resulted in variations in docking interactions. We believe that our approach can be extrapolated to include other viruses to study the clinical significance of genotype-specific variations in drug–protein interactions.
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spelling pubmed-77056712020-12-02 An in silico approach to analyze HCV genotype-specific binding-site variation and its effect on drug–protein interaction Khalid, Ramsha Anwar, Muhammad Faraz Raees, Muhammad Aanish Naeem, Sadaf Abidi, Syed Hani Ali, Syed Sci Rep Article Genotype variation in viruses can affect the response of antiviral treatment. Several studies have established approaches to determine genotype-specific variations; however, analyses to determine the effect of these variations on drug–protein interactions remain unraveled. We present an in-silico approach to explore genotype-specific variations and their effect on drug–protein interaction. We have used HCV NS3 helicase and fluoroquinolones as a model for drug–protein interaction and have investigated the effect of amino acid variations in HCV NS3 of genotype 1a, 1b, 2b and 3a on NS3-fluoroquinolone interaction. We retrieved 687, 667, 101 and 248 nucleotide sequences of HCV NS3 genotypes 1a, 1b, 2b, and 3a, respectively, and translated these into amino acid sequences and used for genotype variation analysis, and also to construct 3D protein models for 2b and 3a genotypes. For 1a and 1b, crystal structures were used. Drug–protein interactions were determined using molecular docking analyses. Our results revealed that individual genotype-specific HCV NS3 showed substantial sequence heterogeneity that resulted in variations in docking interactions. We believe that our approach can be extrapolated to include other viruses to study the clinical significance of genotype-specific variations in drug–protein interactions. Nature Publishing Group UK 2020-11-30 /pmc/articles/PMC7705671/ /pubmed/33257748 http://dx.doi.org/10.1038/s41598-020-77720-9 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Khalid, Ramsha
Anwar, Muhammad Faraz
Raees, Muhammad Aanish
Naeem, Sadaf
Abidi, Syed Hani
Ali, Syed
An in silico approach to analyze HCV genotype-specific binding-site variation and its effect on drug–protein interaction
title An in silico approach to analyze HCV genotype-specific binding-site variation and its effect on drug–protein interaction
title_full An in silico approach to analyze HCV genotype-specific binding-site variation and its effect on drug–protein interaction
title_fullStr An in silico approach to analyze HCV genotype-specific binding-site variation and its effect on drug–protein interaction
title_full_unstemmed An in silico approach to analyze HCV genotype-specific binding-site variation and its effect on drug–protein interaction
title_short An in silico approach to analyze HCV genotype-specific binding-site variation and its effect on drug–protein interaction
title_sort in silico approach to analyze hcv genotype-specific binding-site variation and its effect on drug–protein interaction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7705671/
https://www.ncbi.nlm.nih.gov/pubmed/33257748
http://dx.doi.org/10.1038/s41598-020-77720-9
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