Discovery of promiscuous HLA-II-restricted T cell epitopes with TEPITOPE |
| |
Authors: | Bian Hongjin Hammer Juergen |
| |
Institution: | Section of Bioinformatics, Genetics and Genomics, Hoffmann-La Roche Inc., Nutley, New Jersey, USA. |
| |
Abstract: | 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. |
| |
Keywords: | TEPITOPE HLA-DR Epitope prediction Vaccine Bioinformatics |
本文献已被 ScienceDirect PubMed 等数据库收录! |
|