T‐cell epitopes of the La/SSB autoantigen: Prediction based on the homology modeling of HLA‐DQ2/DQ7 with the insulin‐B peptide/HLA‐DQ8 complex

T‐cell epitopes are important components of the inappropriate response of the immune system to self‐proteins in autoimmune diseases. In this study, the candidate T‐cell epitopes of the La/SSB autoantigen, the main target of the autoimmune response in patients with Sjogren's Syndrome (SS), and Systemic Lupus Erythematosus (SLE) were predicted using as a template the HLA‐DQ2 and DQ7 molecules, which are genetically linked to patients with SS and SLE. Modeling of DQ2 and DQ7 was based on the crystal structure of HLA‐DQ8, an HLA molecule of high risk factor of type I diabetes, which is also an autoimmune disease. The quality and reliability of the modeled DQ2 and DQ7 was confirmed by the Ramachandran plot and the TINKER molecular modeling software. Common and/or similar candidate T‐cell epitopes, obtained by comparing three different approaches the Taylor's sequence pattern, the TEPITOPE quantitative matrices, and the MULTIPRED artificial neural network, were subjected to homology modeling with the crystal structure of the insulin‐B peptide complexed with HLA‐DQ8, and the best superposed candidate epitopes were placed into the modeled HLA‐DQ2 and DQ7 binding grooves to perform energy minimization calculations. Six T‐cell epitopes were predicted for HLA‐DQ7 and nine for HLA‐DQ2 covering parts of the amino‐terminal and the central regions of the La/SSB autoantigen. Residues corresponding to the P1, P4, and P9 pockets of the HLA‐DQ2 and DQ7 binding grooves experience very low SASA because they are less exposed to the microenvironment of the groove. The proposed T‐cell epitopes complexed with HLA‐DQ2/DQ7 were further evaluated for their binding efficiency according to their potential interaction energy, binding affinity, and IC50 values. Our approach constitutes the ground work for a rapid and reliable experimentation concerning the T‐cell epitope mapping of autoantigens, and could lead to the development of T‐cell inhibitors as immunotherapeutics in autoimmune diseases. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 1033–1044, 2006

[1]  Vladimir Brusic,et al.  Computational methods for prediction of T-cell epitopes--a framework for modelling, testing, and applications. , 2004, Methods.

[2]  Melinda Fitzgerald,et al.  Immunol. Cell Biol. , 1995 .

[3]  P. Jensen Peptide binding and antigen presentation by class II histocompatibility glycoproteins. , 1997, Biopolymers.

[4]  M. Karplus,et al.  CHARMM: A program for macromolecular energy, minimization, and dynamics calculations , 1983 .

[5]  Andrew W. Liu,et al.  Rapid epitope identification from complex class-II-restricted T-cell antigens. , 2001, Trends in immunology.

[6]  E. Thorsby,et al.  Evidence for a primary association of celiac disease to a particular HLA-DQ alpha/beta heterodimer , 1989, The Journal of experimental medicine.

[7]  Charles E. Bugg,et al.  Crystallographic and Modeling Methods in Molecular Design , 1990, Springer New York.

[8]  L. Otvos,et al.  Identification of a rabies virus T cell epitope on the basis of its similarity with a hepatitis B surface antigen peptide presented to T cells by the same MHC molecule (HLA-DPw4). , 1990, Journal of immunology.

[9]  Don C. Wiley,et al.  Structure of a human insulin peptide–HLA-DQ8 complex and susceptibility to type 1 diabetes , 2001, Nature Immunology.

[10]  D. Wiley,et al.  A hypothetical model of the foreign antigen binding site of Class II histocompatibility molecules , 1988, Nature.

[11]  Zukang Feng,et al.  The Protein Data Bank and structural genomics , 2003, Nucleic Acids Res..

[12]  Z. Nagy,et al.  Precise prediction of major histocompatibility complex class II-peptide interaction based on peptide side chain scanning , 1994, The Journal of experimental medicine.

[13]  Pingping Guan,et al.  MHCPred: a server for quantitative prediction of peptide-MHC binding , 2003, Nucleic Acids Res..

[14]  Y. Kamisugi,et al.  Parameters determining the efficiency of gene targeting in the moss Physcomitrella patens , 2005, Nucleic acids research.

[15]  U. Şahin,et al.  Generation of tissue-specific and promiscuous HLA ligand databases using DNA microarrays and virtual HLA class II matrices , 1999, Nature Biotechnology.

[16]  Disabling an integral CTL epitope allows suppression of autoimmune diabetes by intranasal proinsulin peptide , 2003 .

[17]  J. Thornton,et al.  PROCHECK: a program to check the stereochemical quality of protein structures , 1993 .

[18]  Don C. Wiley,et al.  Crystal structure of the human class II MHC protein HLA-DR1 complexed with an influenza virus peptide , 1994, Nature.

[19]  F. Arnett,et al.  Gene interaction at HLA-DQ enhances autoantibody production in primary Sjögren's syndrome. , 1986, Science.

[20]  W. C. Still,et al.  Semianalytical treatment of solvation for molecular mechanics and dynamics , 1990 .

[21]  W. Delano The PyMOL Molecular Graphics System (2002) , 2002 .

[22]  J. Reidhaar-Olson,et al.  The use of bioinformatics for identifying class II-restricted T-cell epitopes. , 2003, Methods.

[23]  Thomas L. Madden,et al.  Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. , 1997, Nucleic acids research.

[24]  M. A. Saper,et al.  Structure of the human class I histocompatibility antigen, HLA-A2 , 1987, Nature.

[25]  J. Bodmer,et al.  IMGT/HLA Database - a sequence database for the human major histocompatibility complex , 2000, Nucleic Acids Res..

[26]  Werner Braun,et al.  Exact and efficient analytical calculation of the accessible surface areas and their gradients for macromolecules , 1998 .

[27]  W. C. Still,et al.  The GB/SA Continuum Model for Solvation. A Fast Analytical Method for the Calculation of Approximate Born Radii , 1997 .

[28]  Julie McMurry,et al.  Immuno‐informatics: Mining genomes for vaccine components , 2002, Immunology and cell biology.

[29]  J. Harley,et al.  Cooperative association of T cell beta receptor and HLA-DQ alleles in the production of anti-Ro in systemic lupus erythematosus. , 1994, Clinical immunology and immunopathology.

[30]  A. Tzioufas,et al.  Zinc ion dependent B-cell epitope, associated with primary Sjogren's syndrome, resides within the putative zinc finger domain of Ro60kD autoantigen: physical and immunologic properties. , 2004 .

[31]  C. Ouzounis,et al.  Novel structural features of the human histocompatibility molecules HLA-DQ as revealed by modeling based on the published structure of the related molecule HLA-DR. , 1996, Journal of structural biology.

[32]  J. Hammer,et al.  Discovery of promiscuous HLA-II-restricted T cell epitopes with TEPITOPE. , 2004, Methods.

[33]  E. Bergseng,et al.  Main Chain Hydrogen Bond Interactions in the Binding of Proline-rich Gluten Peptides to the Celiac Disease-associated HLA-DQ2 Molecule* , 2005, Journal of Biological Chemistry.

[34]  Vladimir Brusic,et al.  MHCPEP, a database of MHC-binding peptides: update 1996 , 1997, Nucleic Acids Res..

[35]  W. Delano The PyMOL Molecular Graphics System , 2002 .

[36]  W. Taylor,et al.  A sequence pattern common to T cell epitopes. , 1988, The EMBO journal.

[37]  Pingping Guan,et al.  MHCPred: bringing a quantitative dimension to the online prediction of MHC binding. , 2003, Applied bioinformatics.

[38]  Manuel C. Peitsch,et al.  SWISS-MODEL: an automated protein homology-modeling server , 2003, Nucleic Acids Res..

[39]  Channa K. Hattotuwagama,et al.  Quantitative online prediction of peptide binding to the major histocompatibility complex. , 2004, Journal of molecular graphics & modelling.

[40]  D. Altmann,et al.  What is the basis for HLA-DQ associations with autoimmune disease? , 1991, Immunology today.

[41]  D. Wiley,et al.  The antigenic identity of peptide-MHC complexes: A comparison of the conformations of five viral peptides presented by HLA-A2 , 1993, Cell.

[42]  P. A. Peterson,et al.  Crystal structures of two viral peptides in complex with murine MHC class I H-2Kb. , 1994, Science.

[43]  T. Olsson,et al.  Primarily chronic progressive and relapsing/remitting multiple sclerosis: two immunogenetically distinct disease entities. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[44]  W. Taylor,et al.  Identification of protein sequence homology by consensus template alignment. , 1986, Journal of molecular biology.

[45]  Vladimir Brusic,et al.  Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network , 1998, Bioinform..

[46]  A. Tzioufas,et al.  Linear epitopes of two different autoantigens-La/SSB and myelin basic protein--with a high degree of molecular similarity, cause different humoral immune responses. , 2003 .

[47]  J. Todd,et al.  A molecular basis for MHC class II--associated autoimmunity. , 1988, Science.

[48]  J M Thornton,et al.  Protein structure prediction. , 1998, Current opinion in biotechnology.

[49]  D. Wiley,et al.  Three-dimensional structure of the human class II histocompatibility antigen HLA-DR1 , 1993, Nature.

[50]  N. Guex,et al.  SWISS‐MODEL and the Swiss‐Pdb Viewer: An environment for comparative protein modeling , 1997, Electrophoresis.

[51]  V. Brusic,et al.  Neural network-based prediction of candidate T-cell epitopes , 1998, Nature Biotechnology.

[52]  C. Janeway,et al.  Analysis of structure and function relationships of an autoantigenic peptide of insulin bound to H-2Kd that stimulates CD8 T cells in insulin-dependent diabetes mellitus , 2002, Proceedings of the National Academy of Sciences of the United States of America.