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Title:
An automated prediction of MHC class I-binding peptides based on positional scanning with peptide libraries | Immunogenetics
Description:
Specificities of three mouse major histocompatibility complex (MHC) class I molecules, Kb, Db, and Ld, were analyzed by positional scanning using combinatorial peptide libraries. The result of the analysis was used to create a scoring program to predict MHC-binding peptides in proteins. The capacity of the scoring was then challenged with a number of peptides by comparing the prediction with the experimental binding. The score and the experimental binding exhibited a linear correlation but with substantial deviations of data points. Statistically, for approximately 80% of randomly chosen peptides, MHC-binding capacity could be predicted within one log concentration of peptides for a half-maximal binding. Known cytotoxic T-lymphocyte epitope peptides could be predicted, with a few exceptions. In addition, frequent findings of MHC-binding peptides with incomplete or no anchor amino acid(s) suggested a substantial bias introduced by natural antigen processing in peptide selection by MHC class I molecules.
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article, mhc, class, peptides, peptide, access, kyoto, university, privacy, cookies, content, department, japan, data, information, log, publish, search, prediction, processing, journal, research, immunogenetics, positional, scanning, libraries, udaka, wiesmüller, kienle, mhcbinding, binding, open, predictions, discover, sakyo, germany, tokyo, springer, function, optional, analysis, personal, parties, policy, find, track, automated, ibinding, based, cite,
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natural antigen processing predict mhc-binding peptides month download article/chapter targeted mhc class mhc-binding peptides related subjects mhc class mhc-binding capacity full article pdf combinatorial peptide libraries article immunogenetics aims privacy choices/manage cookies half-maximal binding karl-heinz wiesmüller randomly chosen peptides experimental binding exhibited european economic area anchor amino acid article udaka conditions privacy policy substantial bias introduced peptide libraries accepting optional cookies günther jung ko okumura check access instant access function journal finder publish article log peptide selection stefan kienle hirokazu tamamura article cite processing experimental binding mhc class information privacy policy personal data screening books a affiliations department optional cookies manage preferences hideo yamagishi peter walden subscription content similar content
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headline:An automated prediction of MHC class I-binding peptides based on positional scanning with peptide libraries
description: Specificities of three mouse major histocompatibility complex (MHC) class I molecules, Kb, Db, and Ld, were analyzed by positional scanning using combinatorial peptide libraries. The result of the analysis was used to create a scoring program to predict MHC-binding peptides in proteins. The capacity of the scoring was then challenged with a number of peptides by comparing the prediction with the experimental binding. The score and the experimental binding exhibited a linear correlation but with substantial deviations of data points. Statistically, for approximately 80% of randomly chosen peptides, MHC-binding capacity could be predicted within one log concentration of peptides for a half-maximal binding. Known cytotoxic T-lymphocyte epitope peptides could be predicted, with a few exceptions. In addition, frequent findings of MHC-binding peptides with incomplete or no anchor amino acid(s) suggested a substantial bias introduced by natural antigen processing in peptide selection by MHC class I molecules.
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description: Specificities of three mouse major histocompatibility complex (MHC) class I molecules, Kb, Db, and Ld, were analyzed by positional scanning using combinatorial peptide libraries. The result of the analysis was used to create a scoring program to predict MHC-binding peptides in proteins. The capacity of the scoring was then challenged with a number of peptides by comparing the prediction with the experimental binding. The score and the experimental binding exhibited a linear correlation but with substantial deviations of data points. Statistically, for approximately 80% of randomly chosen peptides, MHC-binding capacity could be predicted within one log concentration of peptides for a half-maximal binding. Known cytotoxic T-lymphocyte epitope peptides could be predicted, with a few exceptions. In addition, frequent findings of MHC-binding peptides with incomplete or no anchor amino acid(s) suggested a substantial bias introduced by natural antigen processing in peptide selection by MHC class I molecules.
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