A computational analysis of the antigenic properties of haemagglutinin in influenza A H3N2.
BACKGROUND
Modelling antigenic shift in influenza A H3N2 can help to predict the efficiency of vaccines. The virus is known to exhibit sudden jumps in antigenic distance, and prediction of such novel strains from amino acid sequence differences remains a challenge.


RESULTS
From analysis of 6624 amino acid sequences of wild-type H3, we propose updates to the frequently referenced list of 131 amino acids located at or near the five identified antibody binding regions in haemagglutinin (HA). We introduce a class of predictive models based on the analysis of amino acid changes in these binding regions, and extend the principle to changes in HA1 as a whole by dividing the molecule into regional bands. Our results show that a range of simple models based on banded changes give better predictive performance than models based on the established five canonical regions and can identify a higher proportion of vaccine escape candidates among novel strains than a current state-of-the-art model.
Lees
William D
WD
Department of Biological Sciences and Institute of Structural and Molecular Biology, Birkbeck College, University of London, Malet Street, London WC1E 7HX, UK. wlees01@mail.cryst.bbk.ac.uk
Moss
David S
DS
Shepherd
Adrian J
AJ
D000595:Amino Acid Sequence; D000940:Antigenic Variation / Q000235:genetics*; D001666:Binding Sites, Antibody; D019295:Computational Biology / Q000379:methods*; D019267:Hemagglutinin Glycoproteins, Influenza Virus / Q000235:genetics*; D006801:Humans; D053122:Influenza A Virus, H3N2 Subtype / Q000235:genetics* / Q000276:immunology*; D007251:Influenza, Human / Q000276:immunology / Q000821:virology; D008958:Models, Molecular; D011487:Protein Conformation
D019267:Hemagglutinin Glycoproteins, Influenza Virus
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