Bioinformatics models for predicting antigenic variants of influenza A/H3N2 virus

Bioinformatics. 2008 Feb 15;24(4):505-12. doi: 10.1093/bioinformatics/btm638. Epub 2008 Jan 10.

Abstract

Motivation: Continual and accumulated mutations in hemagglutinin (HA) protein of influenza A virus generate novel antigenic strains that cause annual epidemics.

Results: We propose a model by incorporating scoring and regression methods to predict antigenic variants. Based on collected sequences of influenza A/H3N2 viruses isolated between 1971 and 2002, our model can be used to accurately predict the antigenic variants in 1999-2004 (agreement rate = 91.67%). Twenty amino acid positions identified in our model contribute significantly to antigenic difference and are potential immunodominant positions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acid Sequence
  • Antigenic Variation / genetics*
  • Antigens, Viral / chemistry
  • Antigens, Viral / genetics*
  • Computational Biology / methods*
  • Hemagglutinin Glycoproteins, Influenza Virus / chemistry
  • Influenza A Virus, H3N2 Subtype / genetics*
  • Models, Molecular
  • Models, Statistical*
  • Molecular Sequence Data
  • Phylogeny
  • Regression Analysis

Substances

  • Antigens, Viral
  • Hemagglutinin Glycoproteins, Influenza Virus