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Structural significance of residues 158-160 in the H3N2 hemagglutnin globular head: A computational study with implications in viral evolution and inf

tetano

Editor, Senior Moderator
J Mol Graph Model. 2019 Feb 25;89:33-40. doi: 10.1016/j.jmgm.2019.02.007. [Epub ahead of print]
[h=1]Structural significance of residues 158-160 in the H3N2 hemagglutnin globular head: A computational study with implications in viral evolution and infection.[/h] Cueno ME[SUP]1[/SUP], Shiotsu H[SUP]2[/SUP], Nakano K[SUP]2[/SUP], Sugiyama E[SUP]3[/SUP], Kikuta M[SUP]3[/SUP], Usui R[SUP]2[/SUP], Oya R[SUP]2[/SUP], Imai K[SUP]4[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Influenza A H3N2 has been linked to annual outbreaks within the human population attributable to continuous structural changes. H3N2 HA contains well identified antigenic sites and receptor-binding sites (RBS) that are possibly correlated to viral evolution and infection. However, the structural significance of amino acid residues associated with both viral evolution and infection were not fully demonstrated. Throughout this study, we generated and analyzed H3N2 HA models that represented the clade 3C.2 population (comprised of clades 3C.2, 3C.2a, and 3C.21 from the transitioning 2014-2018 H3N2 strains) and 3C.3a (from the 2016 H3N2 strain). Model quality estimation, structural analyses and superimposition, and network analytics of H3N2 HA1 evolution were performed. We found that the structural properties of residues 158-160 could influence the overall HA backbone. More specifically, amino acid substitutions at residues 159-160 affected the amino acid orientation at residue 158, thereby, causing the overall HA backbone structure to vary. Our results were consistent with 1968-2018 HA1 evolution. Taken together, we propose that our results would highlight the structural significance of residues 158-160 in HA1 for both antigenic drift and RBS.
Copyright ? 2019 Elsevier Inc. All rights reserved.


[h=4]KEYWORDS:[/h] Hemagglutinin globular head; Influenza A H3N2 subtype; Network analytics; Receptor-binding site; Structural deviation

PMID: 30849718 DOI: 10.1016/j.jmgm.2019.02.007
 
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