TY - GEN
T1 - Understanding prediction systems for HLA-binding peptides and T-Cell epitope identification
AU - You, Liwen
AU - Zhang, Ping
AU - Bodén, Mikael
AU - Brusic, Vladimir
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - Peptide binding to HLA molecules is a critical step in induction and regulation of T-cell mediated immune responses. Because of combinatorial complexity of immune responses, systematic studies require combination of computational methods and experimentation. Most of available computational predictions are based on discriminating binders from non-binders based on use of suitable prediction thresholds. We compared four state-of-the-art binding affinity prediction models and found that nonlinear models show better performance than linear models. A comprehensive analysis of HLA binders (A*0101, A*0201, A*0301, A*1101, A*2402, B*0702, B*0801 and B*1501) showed that non-linear predictors predict peptide binding affinity with high accuracy. The analysis of known T-cell epitopes of survivin and known HIV T-cell epitopes showed lack of correlation between binding affinity and immunogenicity of HLA-presented peptides. T-cell epitopes, therefore, can not be directly determined from binding affinities by simple selection of the highest affinity binders.
AB - Peptide binding to HLA molecules is a critical step in induction and regulation of T-cell mediated immune responses. Because of combinatorial complexity of immune responses, systematic studies require combination of computational methods and experimentation. Most of available computational predictions are based on discriminating binders from non-binders based on use of suitable prediction thresholds. We compared four state-of-the-art binding affinity prediction models and found that nonlinear models show better performance than linear models. A comprehensive analysis of HLA binders (A*0101, A*0201, A*0301, A*1101, A*2402, B*0702, B*0801 and B*1501) showed that non-linear predictors predict peptide binding affinity with high accuracy. The analysis of known T-cell epitopes of survivin and known HIV T-cell epitopes showed lack of correlation between binding affinity and immunogenicity of HLA-presented peptides. T-cell epitopes, therefore, can not be directly determined from binding affinities by simple selection of the highest affinity binders.
UR - http://www.scopus.com/inward/record.url?scp=38349072025&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-75286-8_32
DO - 10.1007/978-3-540-75286-8_32
M3 - Conference contribution
AN - SCOPUS:38349072025
SN - 9783540752851
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 337
EP - 348
BT - Pattern Recognition in Bioinformatics - Second IAPR International Workshop, PRIB 2007, Proceedings
PB - Springer Verlag
T2 - 2nd IAPR International Workshop on Pattern Recognition in Bioinformatics, PRIB 2007
Y2 - 1 October 2007 through 2 October 2007
ER -
