Abstract

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.

Highlights

  • Genetic variability in the viral population can greatly accelerate the rate of viral evolution in response to different selection p­ ressures[1,2]

  • To explore how genotype-specific variations in Hepatitis C virus (HCV) NS3 might affect the inhibition of its activity by fluoroquinolones, we have investigated the effect of active site residue variations in HCV genotype 1a, 1b, 2b and 3a on NS3-fluoroquinolone interactions

  • We present an in-silico approach to assess the effect of genotype-specific amino acid variations on protein folding and structural architecture and its interaction with the drugs

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Summary

Introduction

Genetic variability in the viral population can greatly accelerate the rate of viral evolution in response to different selection p­ ressures[1,2]. The characterization of genomic variations in viral variants is essential to understand various aspects of evolution, persistence, epidemiology, immune escape, and development of antiviral drug r­ esistance[1,2,3,4]. This analysis can identify crucial variations/mutations associated with variability in antiviral treatment response. We present an in-silico approach to explore genotype-specific amino acid variations and their effect on drug–protein interaction. To explore how genotype-specific variations in HCV NS3 might affect the inhibition of its activity by fluoroquinolones, we have investigated the effect of active site residue variations in HCV genotype 1a, 1b, 2b and 3a on NS3-fluoroquinolone interactions

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