EpiTOP—a proteochemometric tool for MHC class II binding prediction

Ivan Dimitrov, Panayot Garnev, Darren R Flower, Irini Doytchinova

Research output: Contribution to journalArticlepeer-review


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.
Original languageEnglish
Article numberbtq324
Pages (from-to)2066-8
Number of pages3
Issue number16
Early online date23 Jun 2010
Publication statusPublished - 15 Aug 2010

Bibliographical note

This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Bioinformatics following peer review. The definitive publisher-authenticated version Dimitrov, I, Garnev, P, Flower, DR & Doytchinova, I 2010, 'EpiTOP—a proteochemometric tool for MHC class II binding prediction', Bioinformatics (Oxford, England), vol 26, no. 16, pp. 2066-8. is available online at:http://bioinformatics.oxfordjournals.org/content/26/16/2066.


  • alleles
  • T-lymphocyte epitopes
  • HLA-DR antigens
  • HLA-DRB1 chains
  • histocompatibility antigens class II
  • ligands
  • peptides
  • software


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