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Molecular Medicine

, Volume 9, Issue 9–12, pp 220–225 | Cite as

A Novel Predictive Technique for the MHC Class II Peptide-Binding Interaction

  • Matthew N Davies
  • Clare E Sansom
  • Claude Beazley
  • David S Moss
Articles

Abstract

Antigenic peptide is presented to a T-cell receptor through the formation of a stable complex with a Major Histocompatibility Complex (MHC) molecule. Various predictive algorithms have been developed to estimate a peptide’s capacity to form a stable complex with a given MHC Class II allele, a technique integral to the strategy of vaccine design. These have previously incorporated such computational techniques as quantitative matrices and neural networks. We have developed a novel predictive technique that uses molecular modeling of predetermined crystal structures to estimate the stability of an MHC Class II peptide complex. This is the 1st structure-based technique, as previous methods have been based on binding data. ROC curves are used to quantify the accuracy of the molecular modeling technique. The novel predictive technique is found to be comparable with the best predictive software currently available.

Notes

Acknowledgments

MN Davies would like to thank the Biotechnology and Biological Sciences Research Council and the Anthony Nolan Research Institute for their financial support. The authors would also like to extend their thanks to Dr Andy Purkiss for his help in setting up the simulations and Dr Paul Travers for his advice on all things immunological.

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Copyright information

© Feinstein Institute for Medical Research 2003

Authors and Affiliations

  • Matthew N Davies
    • 1
  • Clare E Sansom
    • 1
  • Claude Beazley
    • 1
  • David S Moss
    • 1
  1. 1.School of Crystallography, Birkbeck CollegeUniversity of LondonLondonUK

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