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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.

Abstract
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.
AuthorsAggeliki Kosmopoulou, Metaxia Vlassi, Athanassios Stavrakoudis, Constantinos Sakarellos, Maria Sakarellos-Daitsiotis
JournalJournal of computational chemistry (J Comput Chem) Vol. 27 Issue 9 Pg. 1033-44 (Jul 15 2006) ISSN: 0192-8651 [Print] United States
PMID16639700 (Publication Type: Journal Article)
Chemical References
  • Autoantigens
  • Epitopes, T-Lymphocyte
  • HLA-DQ Antigens
  • Insulin
  • Peptide Fragments
  • Ribonucleoproteins
  • SS-B antigen
Topics
  • Amino Acid Sequence
  • Autoantigens (chemistry, immunology)
  • Computer Simulation
  • Crystallography, X-Ray
  • Epitopes, T-Lymphocyte (chemistry, immunology)
  • HLA-DQ Antigens (chemistry, immunology)
  • Humans
  • Insulin (chemistry, immunology)
  • Models, Molecular
  • Molecular Sequence Data
  • Peptide Fragments (chemistry, immunology)
  • Protein Binding
  • Protein Structure, Quaternary
  • Protein Structure, Tertiary
  • Ribonucleoproteins (chemistry, immunology)
  • Sequence Alignment
  • Software
  • Structural Homology, Protein

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