Abstract
Motivation: T-cell epitope identification is a critical immunoinformatic 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. © The Author 2010. Published by Oxford University Press. All rights reserved.
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CITATION STYLE
Dimitrov, I., Garnev, P., Flower, D. R., & Doytchinova, I. (2010). EpiTOP-a proteochemometric tool for MHC class II binding prediction. Bioinformatics, 26(16), 2066–2068. https://doi.org/10.1093/bioinformatics/btq324
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