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Immunogenetics

, Volume 57, Issue 5, pp 304–314 | Cite as

Automated generation and evaluation of specific MHC binding predictive tools: ARB matrix applications

  • Huynh-Hoa Bui
  • John Sidney
  • Bjoern Peters
  • Muthuraman Sathiamurthy
  • Asabe Sinichi
  • Kelly-Anne Purton
  • Bianca R. Mothé
  • Francis V. Chisari
  • David I. Watkins
  • Alessandro Sette
Original Paper

Abstract

Prediction of which peptides can bind major histocompatibility complex (MHC) molecules is commonly used to assist in the identification of T cell epitopes. However, because of the large numbers of different MHC molecules of interest, each associated with different predictive tools, tool generation and evaluation can be a very resource intensive task. A methodology commonly used to predict MHC binding affinity is the matrix or linear coefficients method. Herein, we described Average Relative Binding (ARB) matrix methods that directly predict IC50 values allowing combination of searches involving different peptide sizes and alleles into a single global prediction. A computer program was developed to automate the generation and evaluation of ARB predictive tools. Using an in-house MHC binding database, we generated a total of 85 and 13 MHC class I and class II matrices, respectively. Results from the automated evaluation of tool efficiency are presented. We anticipate that this automation framework will be generally applicable to the generation and evaluation of large numbers of MHC predictive methods and tools, and will be of value to centralize and rationalize the process of evaluation of MHC predictions. MHC binding predictions based on ARB matrices were made available at http://epitope.liai.org:8080/matrix web server.

Keywords

MHC Binding prediction Computer algorithms Automated tool evaluation Web server 

Notes

Acknowledgements

This work was supported by the National Institutes of Health’s contract HHSN26620040006C (Immune Epitope Database and Analysis Program) and grant R24 RR15371 (MHC Bound, SIV Derived, CTL and HTL Epitopes).

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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • Huynh-Hoa Bui
    • 1
  • John Sidney
    • 1
  • Bjoern Peters
    • 1
  • Muthuraman Sathiamurthy
    • 1
  • Asabe Sinichi
    • 2
  • Kelly-Anne Purton
    • 2
  • Bianca R. Mothé
    • 1
  • Francis V. Chisari
    • 2
  • David I. Watkins
    • 3
  • Alessandro Sette
    • 1
  1. 1.Division of Vaccine DiscoveryLa Jolla Institute for Allergy and ImmunologySan DiegoUSA
  2. 2.Division of Experimental PathologyThe Scripps Research InstituteLa JollaUSA
  3. 3.Wisconsin Regional Primate CenterUniversity of WisconsinMadisonUSA

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