期刊
BIOINFORMATICS
卷 26, 期 16, 页码 2066-2068出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btq324
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资金
- Ministry of Education and Science, Bulgaria [02-115/2008]
- Wellcome Trust [WT079287MA]
Motivation: T-cell epitope identification is a critical immuno-informatic problem within vaccine design. To be an epitope, a peptide must bind an MHC protein. Results: Here, we present EpiTOP, the first server predicting MHC class II binding based on proteochemometrics, a QSAR approach for ligands binding to several related proteins. EpiTOP uses a quantitative matrix to predict binding to 12 HLA-DRB1 alleles. It identifies 89% of known epitopes within the top 20% of predicted binders, reducing laboratory labour, materials and time by 80%. EpiTOP is easy to use, gives comprehensive quantitative predictions and will be expanded and updated with new quantitative matrices over time.
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