Predicting Antigenic Variants of Influenza A/H3N2 Viruses
Current inactivated influenza vaccines provide protection when vaccine antigens and circulating viruses share a high degree of similarity in hemagglutinin protein. Five antigenic sites in the hemagglutinin protein have been proposed, and 131 amino acid positions have been identified in the five anti...
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Centers for Disease Control and Prevention
2004-08-01
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doaj-9bf6595ec826444aba4cc133a1c0c4d02020-11-25T01:58:09ZengCenters for Disease Control and PreventionEmerging Infectious Diseases1080-60401080-60592004-08-011081385139010.3201/eid1008.040107Predicting Antigenic Variants of Influenza A/H3N2 VirusesMin-Shi LeeJack Si-En ChenCurrent inactivated influenza vaccines provide protection when vaccine antigens and circulating viruses share a high degree of similarity in hemagglutinin protein. Five antigenic sites in the hemagglutinin protein have been proposed, and 131 amino acid positions have been identified in the five antigenic sites. In addition, 20, 18, and 32 amino acid positions in the hemagglutinin protein have been identified as mouse monoclonal antibody–binding sites, positively selected codons, and substantially diverse codons, respectively. We investigated these amino acid positions for predicting antigenic variants of influenza A/H3N2 viruses in ferrets. Results indicate that the model based on the number of amino acid changes in the five antigenic sites is best for predicting antigenic variants (agreement = 83%). The methods described in this study could be applied to predict vaccine-induced cross-reactive antibody responses in humans, which may further improve the selection of vaccine strains.https://wwwnc.cdc.gov/eid/article/10/8/04-0107_articleinfluenzaantigenicityvaccine strainhemagglutininprediction modelantigenic variants |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Min-Shi Lee Jack Si-En Chen |
spellingShingle |
Min-Shi Lee Jack Si-En Chen Predicting Antigenic Variants of Influenza A/H3N2 Viruses Emerging Infectious Diseases influenza antigenicity vaccine strain hemagglutinin prediction model antigenic variants |
author_facet |
Min-Shi Lee Jack Si-En Chen |
author_sort |
Min-Shi Lee |
title |
Predicting Antigenic Variants of Influenza A/H3N2 Viruses |
title_short |
Predicting Antigenic Variants of Influenza A/H3N2 Viruses |
title_full |
Predicting Antigenic Variants of Influenza A/H3N2 Viruses |
title_fullStr |
Predicting Antigenic Variants of Influenza A/H3N2 Viruses |
title_full_unstemmed |
Predicting Antigenic Variants of Influenza A/H3N2 Viruses |
title_sort |
predicting antigenic variants of influenza a/h3n2 viruses |
publisher |
Centers for Disease Control and Prevention |
series |
Emerging Infectious Diseases |
issn |
1080-6040 1080-6059 |
publishDate |
2004-08-01 |
description |
Current inactivated influenza vaccines provide protection when vaccine antigens and circulating viruses share a high degree of similarity in hemagglutinin protein. Five antigenic sites in the hemagglutinin protein have been proposed, and 131 amino acid positions have been identified in the five antigenic sites. In addition, 20, 18, and 32 amino acid positions in the hemagglutinin protein have been identified as mouse monoclonal antibody–binding sites, positively selected codons, and substantially diverse codons, respectively. We investigated these amino acid positions for predicting antigenic variants of influenza A/H3N2 viruses in ferrets. Results indicate that the model based on the number of amino acid changes in the five antigenic sites is best for predicting antigenic variants (agreement = 83%). The methods described in this study could be applied to predict vaccine-induced cross-reactive antibody responses in humans, which may further improve the selection of vaccine strains. |
topic |
influenza antigenicity vaccine strain hemagglutinin prediction model antigenic variants |
url |
https://wwwnc.cdc.gov/eid/article/10/8/04-0107_article |
work_keys_str_mv |
AT minshilee predictingantigenicvariantsofinfluenzaah3n2viruses AT jacksienchen predictingantigenicvariantsofinfluenzaah3n2viruses |
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