Computational analysis and modeling the effectiveness of 'Zanamivir' targeting neuraminidase protein in pandemic H1N1 strains

Shailendra K. Gupta, Shishir K. Gupta, Suchi Smita, Mugdha Srivastava, Xin Lai, Ulf Schmitz, Qamar Rahman, Olaf Wolkenhauer, Julio Vera

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)

Abstract

Antigenic drift causes number of mutations in neuraminidase protein of H1N1 swine influenza virus. We analyzed neuraminidase mutations in H1N1 strains distributed over six continents, at both the sequence and structural level. Mutations in the nearby residues of the drug binding site play crucial role in the binding affinity of the drug with the protein. For this purpose, mutant models were generated for the neuraminidase protein from 34 pandemic H1N1 isolates and docking were performed with zanamivir drug. Multiple sequence alignment (MSA) and variations in docking score suggest that there are considerable changes in the binding affinity of neuraminidase with zanamivir, which leads to probable ineffectiveness of zanamivir in the isolated samples of pandemic H1N1 collected from quite a few countries. To further evaluate the effectiveness of the antiviral drugs, we derived, calibrated and analyzed an ordinary differential equations based mathematical model for H1N1 infection dynamics and drug mediated virus deactivation.

Original languageEnglish
Pages (from-to)1072-1082
Number of pages11
JournalInfection, Genetics and Evolution
Volume11
Issue number5
DOIs
Publication statusPublished - Jul 2011
Externally publishedYes
Publication typeA1 Journal article-refereed

Keywords

  • Antigenic drift
  • Drug interaction
  • H1N1 Influenza virus
  • Mathematical model
  • Neuraminidase
  • Swine flu
  • Zanamivir

ASJC Scopus subject areas

  • Microbiology
  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics
  • Microbiology (medical)
  • Infectious Diseases

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