tetano
Editor, Senior Moderator
Sci Rep. 2016 Aug 8;6:31156. doi: 10.1038/srep31156.
[h=1]Incorporating structure context of HA protein to improve antigenicity calculation for influenza virus A/H3N2.[/h] Qiu J[SUP]1[/SUP], Qiu T[SUP]1[/SUP], Yang Y[SUP]1[/SUP], Wu D[SUP]1[/SUP], Cao Z[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] The rapid and consistent mutation of influenza requires frequent evaluation of antigenicity variation among newly emerged strains, during which several in-silico methods have been reported to facilitate the assays. In this paper, we designed a structure-based antigenicity scoring model instead of those sequence-based previously published. Protein structural context was adopted to derive the antigenicity-dominant positions, as well as the physic-chemical change of local micro-environment in correlation with antigenicity change. Then a position specific scoring matrix (PSSM) profile and local environmental change over above positions were integrated to predict the antigenicity variance. Independent testing showed a high accuracy of 0.875, and sensitivity of 0.986, with a significant ability to discover antigenic-escaping strains. When applying this model to the historical data, global and regional antigenic drift events can be successfully detected. Furthermore, two well-known vaccine failure events were clearly suggested. Therefore, this structure-context model may be particularly useful to identify those to-be-failed vaccine strains, in addition to suggest potential new vaccine strains.
PMID: 27498613 DOI: 10.1038/srep31156
[PubMed - in process] Free full text
[h=1]Incorporating structure context of HA protein to improve antigenicity calculation for influenza virus A/H3N2.[/h] Qiu J[SUP]1[/SUP], Qiu T[SUP]1[/SUP], Yang Y[SUP]1[/SUP], Wu D[SUP]1[/SUP], Cao Z[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] The rapid and consistent mutation of influenza requires frequent evaluation of antigenicity variation among newly emerged strains, during which several in-silico methods have been reported to facilitate the assays. In this paper, we designed a structure-based antigenicity scoring model instead of those sequence-based previously published. Protein structural context was adopted to derive the antigenicity-dominant positions, as well as the physic-chemical change of local micro-environment in correlation with antigenicity change. Then a position specific scoring matrix (PSSM) profile and local environmental change over above positions were integrated to predict the antigenicity variance. Independent testing showed a high accuracy of 0.875, and sensitivity of 0.986, with a significant ability to discover antigenic-escaping strains. When applying this model to the historical data, global and regional antigenic drift events can be successfully detected. Furthermore, two well-known vaccine failure events were clearly suggested. Therefore, this structure-context model may be particularly useful to identify those to-be-failed vaccine strains, in addition to suggest potential new vaccine strains.
PMID: 27498613 DOI: 10.1038/srep31156
[PubMed - in process] Free full text