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A computer program for predicting possible cytotoxic T lymphocyte epitopes based on HLA class I peptide-binding motifs

Identifieur interne : 004106 ( Main/Exploration ); précédent : 004105; suivant : 004107

A computer program for predicting possible cytotoxic T lymphocyte epitopes based on HLA class I peptide-binding motifs

Auteurs : Joe D'Amaro [Pays-Bas] ; Jos G. A. Houbiers [Pays-Bas] ; Jan W. Drijfhout [Pays-Bas] ; Remco M. P. Brandt [Pays-Bas] ; Ronald Schipper [Pays-Bas] ; Jan N. Bouwes Bavinck [Pays-Bas] ; Cornelis J. M. Melief [Pays-Bas] ; W. Martin Kast [Pays-Bas]

Source :

RBID : ISTEX:043E155696AE8A9AB274C51B02DA7A7AEB70A2CB

English descriptors

Abstract

Abstract: Vaccination with peptides recognized by antigen-specific CTLs can prevent lethal virus infections and tumor growth. In order to avoid the synthesis and testing of the numerous overlapping peptides of long AA sequences of proteins of interest, we developed a computer program which utilizes the rules, “motifs” which govern how peptides bind to HLA class I molecules, to derive a predicted binding score for each overlapping peptide. Correlations between the predicted and actual binding results to HLA-A∗0201 for 100 peptides selected from six early and two late protein sequences of human papilloma-virus type la revealed an acceptable level (61%) of concordance. The program is very flexible with regard to the input of protein sequences and motif definitions and is able to handle various motif and peptide lengths.

Url:
DOI: 10.1016/0198-8859(94)00153-H


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

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<div type="abstract" xml:lang="en">Abstract: Vaccination with peptides recognized by antigen-specific CTLs can prevent lethal virus infections and tumor growth. In order to avoid the synthesis and testing of the numerous overlapping peptides of long AA sequences of proteins of interest, we developed a computer program which utilizes the rules, “motifs” which govern how peptides bind to HLA class I molecules, to derive a predicted binding score for each overlapping peptide. Correlations between the predicted and actual binding results to HLA-A∗0201 for 100 peptides selected from six early and two late protein sequences of human papilloma-virus type la revealed an acceptable level (61%) of concordance. The program is very flexible with regard to the input of protein sequences and motif definitions and is able to handle various motif and peptide lengths.</div>
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