Quantitative online prediction of peptide binding to the major histocompatibility complex

Channa K. Hattotuwagama, Pingping Guan, Irini A. Doytchinova, Christianna Zygouri, Darren R. Flower

Research output: Contribution to journalArticlepeer-review

Abstract

With its implications for vaccine discovery, the accurate prediction of T cell epitopes is one of the key aspirations of computational vaccinology. We have developed a robust multivariate statistical method, based on partial least squares, for the quantitative prediction of peptide binding to major histocompatibility complexes (MHC), the principal checkpoint on the antigen presentation pathway. As a service to the immunobiology community, we have made a Perl implementation of the method available via a World Wide Web server. We call this server MHCPred. Access to the server is freely available from the URL: http://www.jenner.ac.uk/MHCPred. We have exemplified our method with a model for peptides binding to the common human MHC molecule HLA-B*3501.
Original languageEnglish
Pages (from-to)195-207
Number of pages13
JournalJournal of Molecular Graphics and Modelling
Volume22
Issue number3
Early online date26 Aug 2003
DOIs
Publication statusPublished - Jan 2004

Keywords

  • peptide binding
  • partial least squares
  • quantitative structure activity relationships
  • T cell epitope
  • major histocompatibility complex

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