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Methods. 2004 Dec;34(4):468-75.

Discovery of promiscuous HLA-II-restricted T cell epitopes with TEPITOPE.

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  • 1Section of Bioinformatics, Genetics and Genomics, Hoffmann-La Roche Inc., Nutley, New Jersey, USA.


TEPITOPE is a prediction model that has been successfully applied to the in silico identification of T cell epitopes in the context of oncology, allergy, infectious diseases, and autoimmune diseases. Like most epitope prediction models, TEPITOPE's underlying algorithm is based on the prediction of HLA-II peptide binding, which constitutes a major bottleneck in the natural selection of epitopes. An important step in the design of subunit vaccines is the identification of promiscuous HLA-II ligands in sets of disease-specific gene products. TEPITOPE's user interface enables the systematic prediction of promiscuous peptide ligands for a broad range of HLA-binding specificity. We show how to apply the TEPITOPE prediction model to identify T cell epitopes, and provide both a road map and examples of its successful application.

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