Quantitative online prediction of peptide binding to the major histocompatibility complex.

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.

[1]  Irini Doytchinova,et al.  The HLA-A2-supermotif: a QSAR definition. , 2003, Organic & biomolecular chemistry.

[2]  D. Flower,et al.  Physicochemical explanation of peptide binding to HLA‐A*0201 major histocompatibility complex: A three‐dimensional quantitative structure‐activity relationship study , 2002, Proteins.

[3]  F. Sinigaglia,et al.  Motifs and supermotifs for MHC class II binding peptides , 1995, The Journal of experimental medicine.

[4]  K. Parker,et al.  Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains. , 1994, Journal of immunology.

[5]  M. Reddehase,et al.  Two Antigenic Peptides from Genes m123 and m164 of Murine Cytomegalovirus Quantitatively Dominate CD8 T-Cell Memory in the H-2d Haplotype , 2002, Journal of Virology.

[6]  Gajendra P. S. Raghava,et al.  ProPred: prediction of HLA-DR binding sites , 2001, Bioinform..

[7]  H. Grey,et al.  Prediction of major histocompatibility complex binding regions of protein antigens by sequence pattern analysis. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[8]  W R Taylor,et al.  Location of ‘continuous’ antigenic determinants in the protruding regions of proteins. , 1986, The EMBO journal.

[9]  Pingping Guan,et al.  HLA-A3 supermotif defined by quantitative structure-activity relationship analysis. , 2003, Protein engineering.

[10]  M F del Guercio,et al.  Several HLA alleles share overlapping peptide specificities. , 1995, Journal of immunology.

[11]  S. Wold,et al.  Peptide quantitative structure-activity relationships, a multivariate approach. , 1987, Journal of medicinal chemistry.

[12]  Y. Cheng,et al.  Relationship between the inhibition constant (K1) and the concentration of inhibitor which causes 50 per cent inhibition (I50) of an enzymatic reaction. , 1973, Biochemical pharmacology.

[13]  A. Tropsha,et al.  Beware of q2! , 2002, Journal of molecular graphics & modelling.

[14]  J. Sidney,et al.  Prominent role of secondary anchor residues in peptide binding to HLA-A2.1 molecules , 1993, Cell.

[15]  Bruce L. Bush,et al.  Sample-distance partial least squares: PLS optimized for many variables, with application to CoMFA , 1993, J. Comput. Aided Mol. Des..

[16]  J. Drijfhout,et al.  A computer program for predicting possible cytotoxic T lymphocyte epitopes based on HLA class I peptide-binding motifs. , 1995, Human immunology.

[17]  L. Zhihua,et al.  Toward the quantitative prediction of T-cell epitopes: QSAR studies on peptides having affinity with the class I MHC molecular HLA-A*0201. , 2004, Journal of computational biology : a journal of computational molecular cell biology.

[18]  S. Wold,et al.  New chemical descriptors relevant for the design of biologically active peptides. A multivariate characterization of 87 amino acids. , 1998, Journal of medicinal chemistry.

[19]  D. Flower,et al.  Additive method for the prediction of protein-peptide binding affinity. Application to the MHC class I molecule HLA-A*0201. , 2002, Journal of proteome research.

[20]  W. Saenger,et al.  Decamer-like conformation of a nona-peptide bound to HLA-B*3501 due to non-standard positioning of the C terminus. , 1998, Journal of molecular biology.

[21]  D. Flower,et al.  Toward the quantitative prediction of T-cell epitopes: coMFA and coMSIA studies of peptides with affinity for the class I MHC molecule HLA-A*0201. , 2001, Journal of medicinal chemistry.

[22]  A. Vitiello,et al.  The relationship between class I binding affinity and immunogenicity of potential cytotoxic T cell epitopes. , 1994, Journal of immunology.

[23]  M F del Guercio,et al.  Specificity and degeneracy in peptide binding to HLA-B7-like class I molecules. , 1996, Journal of immunology.

[24]  A. Alix,et al.  Predictive estimation of protein linear epitopes by using the program PEOPLE. , 1999, Vaccine.

[25]  E Westhof,et al.  PREDITOP: a program for antigenicity prediction. , 1993, Journal of molecular graphics.

[26]  R W Chesnut,et al.  Human histocompatibility leukocyte antigen-binding supermotifs predict broadly cross-reactive cytotoxic T lymphocyte responses in patients with acute hepatitis. , 1997, The Journal of clinical investigation.

[27]  M. Reddehase,et al.  Early gene m18, a novel player in the immune response to murine cytomegalovirus. , 2002, The Journal of general virology.

[28]  S Ferrone,et al.  HLA-B*3501-peptide interactions: role of anchor residues of peptides in their binding to HLA-B*3501 molecules. , 1994, International immunology.

[29]  Irini A. Doytchinova,et al.  JenPep: a database of quantitative functional peptide data for immunology , 2002, Bioinform..

[30]  D I Stuart,et al.  An altered position of the alpha 2 helix of MHC class I is revealed by the crystal structure of HLA-B*3501. , 1996, Immunity.

[31]  H. Rammensee,et al.  SYFPEITHI: database for MHC ligands and peptide motifs , 1999, Immunogenetics.

[32]  Steven A. Rosenberg,et al.  Identification of a MHC Class II-Restricted Human gp100 Epitope Using DR4-IE Transgenic Mice , 2000, The Journal of Immunology.

[33]  G. Jung,et al.  From combinatorial libraries to MHC ligand motifs, T-cell superagonists and antagonists. , 2001, Biologicals : journal of the International Association of Biological Standardization.

[34]  John Sidney,et al.  Structural Features of Peptide Analogs of Human Histocompatibility Leukocyte Antigen Class I Epitopes That Are More Potent and Immunogenic than Wild-Type Peptide , 2001, The Journal of experimental medicine.

[35]  Martin T. Swain,et al.  An automated approach to modelling class II MHC alleles and predicting peptide binding , 2001, Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001).

[36]  Irini A. Doytchinova,et al.  Computational vaccine design , 2002 .

[37]  R W Chesnut,et al.  Degenerate cytotoxic T cell epitopes from P. falciparum restricted by multiple HLA-A and HLA-B supertype alleles. , 1997, Immunity.