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GPS-MBA: Computational Analysis of MHC Class II Epitopes in Type 1 Diabetes

Author

Listed:
  • Ruikun Cai
  • Zexian Liu
  • Jian Ren
  • Chuang Ma
  • Tianshun Gao
  • Yanhong Zhou
  • Qing Yang
  • Yu Xue

Abstract

As a severe chronic metabolic disease and autoimmune disorder, type 1 diabetes (T1D) affects millions of people world-wide. Recent advances in antigen-based immunotherapy have provided a great opportunity for further treating T1D with a high degree of selectivity. It is reported that MHC class II I-Ag7 in the non-obese diabetic (NOD) mouse and human HLA-DQ8 are strongly linked to susceptibility to T1D. Thus, the identification of new I-Ag7 and HLA-DQ8 epitopes would be of great help to further experimental and biomedical manipulation efforts. In this study, a novel GPS-MBA (MHC Binding Analyzer) software package was developed for the prediction of I-Ag7 and HLA-DQ8 epitopes. Using experimentally identified epitopes as the training data sets, a previously developed GPS (Group-based Prediction System) algorithm was adopted and improved. By extensive evaluation and comparison, the GPS-MBA performance was found to be much better than other tools of this type. With this powerful tool, we predicted a number of potentially new I-Ag7 and HLA-DQ8 epitopes. Furthermore, we designed a T1D epitope database (TEDB) for all of the experimentally identified and predicted T1D-associated epitopes. Taken together, this computational prediction result and analysis provides a starting point for further experimental considerations, and GPS-MBA is demonstrated to be a useful tool for generating starting information for experimentalists. The GPS-MBA is freely accessible for academic researchers at: http://mba.biocuckoo.org.

Suggested Citation

  • Ruikun Cai & Zexian Liu & Jian Ren & Chuang Ma & Tianshun Gao & Yanhong Zhou & Qing Yang & Yu Xue, 2012. "GPS-MBA: Computational Analysis of MHC Class II Epitopes in Type 1 Diabetes," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-9, March.
  • Handle: RePEc:plo:pone00:0033884
    DOI: 10.1371/journal.pone.0033884
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    References listed on IDEAS

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    1. Jeffrey A. Bluestone & Kevan Herold & George Eisenbarth, 2010. "Genetics, pathogenesis and clinical interventions in type 1 diabetes," Nature, Nature, vol. 464(7293), pages 1293-1300, April.
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    Cited by:

    1. Ashley I Heinson & Rob M Ewing & John W Holloway & Christopher H Woelk & Mahesan Niranjan, 2019. "An evaluation of different classification algorithms for protein sequence-based reverse vaccinology prediction," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-13, December.

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