The JI
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     
 

This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Doytchinova, I. A.
Right arrow Articles by Flower, D. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Doytchinova, I. A.
Right arrow Articles by Flower, D. R.
The Journal of Immunology, 2004, 172: 7495-7502.
Copyright © 2004 by The American Association of Immunologists

Coupling In Silico and In Vitro Analysis of Peptide-MHC Binding: A Bioinformatic Approach Enabling Prediction of Superbinding Peptides and Anchorless Epitopes

Irini A. Doytchinova1, Valerie A. Walshe1, Nicola A. Jones2, Simone E. Gloster3, Persephone Borrow and Darren R. Flower4

Edward Jenner Institute for Vaccine Research Compton, Berkshire, United Kingdom

The ability to define and manipulate the interaction of peptides with MHC molecules has immense immunological utility, with applications in epitope identification, vaccine design, and immunomodulation. However, the methods currently available for prediction of peptide-MHC binding are far from ideal. We recently described the application of a bioinformatic prediction method based on quantitative structure-affinity relationship methods to peptide-MHC binding. In this study we demonstrate the predictivity and utility of this approach. We determined the binding affinities of a set of 90 nonamer peptides for the MHC class I allele HLA-A*0201 using an in-house, FACS-based, MHC stabilization assay, and from these data we derived an additive quantitative structure-affinity relationship model for peptide interaction with the HLA-A*0201 molecule. Using this model we then designed a series of high affinity HLA-A2-binding peptides. Experimental analysis revealed that all these peptides showed high binding affinities to the HLA-A*0201 molecule, significantly higher than the highest previously recorded. In addition, by the use of systematic substitution at principal anchor positions 2 and 9, we showed that high binding peptides are tolerant to a wide range of nonpreferred amino acids. Our results support a model in which the affinity of peptide binding to MHC is determined by the interactions of amino acids at multiple positions with the MHC molecule and may be enhanced by enthalpic cooperativity between these component interactions.




This article has been cited by other articles:


Home page
 J. Gen. Virol.Home page
R. J. P. Brown, V. S. Juttla, A. W. Tarr, R. Finnis, W. L. Irving, S. Hemsley, D. R. Flower, P. Borrow, and J. K. Ball
Evolutionary dynamics of hepatitis C virus envelope genes during chronic infection
J. Gen. Virol., July 1, 2005; 86(7): 1931 - 1942.
[Abstract] [Full Text] [PDF]

Home page
 J. Immunol.Home page
I. A. Doytchinova and D. R. Flower
In Silico Identification of Supertypes for Class II MHCs
J. Immunol., June 1, 2005; 174(11): 7085 - 7095.
[Abstract] [Full Text] [PDF]

Home page
 J. Immunol.Home page
I. Doytchinova, S. Hemsley, and D. R. Flower
Transporter Associated with Antigen Processing Preselection of Peptides Binding to the MHC: A Bioinformatic Evaluation
J. Immunol., December 1, 2004; 173(11): 6813 - 6819.
[Abstract] [Full Text] [PDF]


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
This Website Copyright © 2004 by The American Association of Immunologists, Inc. All rights reserved.
All Contents Copyright © 2004 by The American Association of Immunologists, Inc. All rights reserved.