Bioinformatics models for predicting antigenic variants of influenza A/H3N2 virus.
BACKGROUND
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.
Liao
Yu-Chieh
YC
Division of Biostatistics and Bioinformatics, National Health Research Institutes, Zhunan 350, Taiwan.
Lee
Min-Shi
MS
Ko
Chin-Yu
CY
Hsiung
Chao A
CA
D000595:Amino Acid Sequence; D000940:Antigenic Variation / Q000235:genetics*; D000956:Antigens, Viral / Q000737:chemistry / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D019267:Hemagglutinin Glycoproteins, Influenza Virus / Q000737:chemistry; D053122:Influenza A Virus, H3N2 Subtype / Q000235:genetics*; D008958:Models, Molecular; D015233:Models, Statistical; D008969:Molecular Sequence Data; D010802:Phylogeny; D012044:Regression Analysis
D000956:Antigens, Viral; D019267:Hemagglutinin Glycoproteins, Influenza Virus