A computational method for identification of vaccine targets from protein regions of conserved human leukocyte antigen binding

TY - JOUR

T1 - A computational method for identification of vaccine targets from protein regions of conserved human leukocyte antigen binding

AU - Olsen, Lars Rønn

AU - Simon, Christian

AU - Kudahl, Ulrich J.

AU - Bagger, Frederik Otzen

AU - Winther, Ole

AU - Reinherz, Ellis L.

AU - Zhang, Guang L.

AU - Brusic, Vladimir

PY - 2015

Y1 - 2015

N2 - Background: Computational methods for T cell-based vaccine target discovery focus on selection of highly conserved peptides identified across pathogen variants, followed by prediction of their binding of human leukocyte antigen molecules. However, experimental studies have shown that T cells often target diverse regions in highly variable viral pathogens and this diversity may need to be addressed through redefinition of suitable peptide targets. Methods: We have developed a method for antigen assessment and target selection for polyvalent vaccines, with which we identified immune epitopes from variable regions, where all variants bind HLA. These regions, although variable, can thus be considered stable in terms of HLA binding and represent valuable vaccine targets. Results: We applied this method to predict CD8+ T-cell targets in influenza A H7N9 hemagglutinin and significantly increased the number of potential vaccine targets compared to the number of targets discovered using the traditional approach where low-frequency peptides are excluded. Conclusions: We developed a webserver with an intuitive visualization scheme for summarizing the T cell-based antigenic potential of any given protein or proteome using human leukocyte antigen binding predictions and made a web-accessible software implementation freely available at http://met-hilab.cbs.dtu.dk/blockcons/.

AB - Background: Computational methods for T cell-based vaccine target discovery focus on selection of highly conserved peptides identified across pathogen variants, followed by prediction of their binding of human leukocyte antigen molecules. However, experimental studies have shown that T cells often target diverse regions in highly variable viral pathogens and this diversity may need to be addressed through redefinition of suitable peptide targets. Methods: We have developed a method for antigen assessment and target selection for polyvalent vaccines, with which we identified immune epitopes from variable regions, where all variants bind HLA. These regions, although variable, can thus be considered stable in terms of HLA binding and represent valuable vaccine targets. Results: We applied this method to predict CD8+ T-cell targets in influenza A H7N9 hemagglutinin and significantly increased the number of potential vaccine targets compared to the number of targets discovered using the traditional approach where low-frequency peptides are excluded. Conclusions: We developed a webserver with an intuitive visualization scheme for summarizing the T cell-based antigenic potential of any given protein or proteome using human leukocyte antigen binding predictions and made a web-accessible software implementation freely available at http://met-hilab.cbs.dtu.dk/blockcons/.

KW - bioinformatics

KW - conservation analysis

KW - cross-reactivity

KW - epitope prediction

KW - T cell immunity

U2 - 10.1186/1755-8794-8-S4-S1

DO - 10.1186/1755-8794-8-S4-S1

M3 - Journal article

C2 - 26679766

AN - SCOPUS:84962361636

SN - 1755-8794

VL - 8

JO - B M C Medical Genomics

JF - B M C Medical Genomics

IS - Suppl 4

M1 - 5

ER -