Prediction of HLA-DQ3.2β ligands: Evidence of multiple registers in class II binding peptides

Joo Chuan Tong, Guang Lan Zhang, Tin Wee Tan, J. Thomas August, Vladimir Brusic, Shoba Ranganathan

Research output: Contribution to journalArticle

38 Citations (Scopus)

Abstract

Motivation: While processing of MHC class II antigens for presentation to helper T-cells is essential for normal immune response, it is also implicated in the pathogenesis of autoimmune disorders and hypersensitivity reactions. Sequence-based computational techniques for predicting HLA-DQ binding peptides have encountered limited success, with few prediction techniques developed using three-dimensional models. Methods: We describe a structure-based prediction model for modeling peptide-DQ3.2β complexes. We have developed a rapid and accurate protocol for docking candidate peptides into the DQ3.2β receptor and a scoring function to discriminate binders from the background. The scoring function was rigorously trained, tested and validated using experimentally verified DQ3.2β binding and non-binding peptides obtained from biochemical and functional studies. Results: Our model predicts DQ3.2β binding peptides with high accuracy [area under the receiver operating characteristic (ROC) curve AROC > 0.90], compared with experimental data. We investigated the binding patterns of DQ3.2β peptides and illustrate that several registers exist within a candidate binding peptide. Further analysis reveals that peptides with multiple registers occur predominantly for high-affinity binders.

Original languageEnglish
Pages (from-to)1232-1238
Number of pages7
JournalBioinformatics
Volume22
Issue number10
DOIs
Publication statusPublished - May 15 2006
Externally publishedYes

Fingerprint

Peptides
Ligands
Prediction
Scoring
Binders
HLA-DQ Antigens
T-cells
Class
Evidence
Docking
Computational Techniques
Immune Response
Histocompatibility Antigens Class II
Receiver Operating Characteristic Curve
Antigen Presentation
Antigens
Helper-Inducer T-Lymphocytes
ROC Curve
Prediction Model
Receptor

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

Tong, J. C., Zhang, G. L., Tan, T. W., August, J. T., Brusic, V., & Ranganathan, S. (2006). Prediction of HLA-DQ3.2β ligands: Evidence of multiple registers in class II binding peptides. Bioinformatics, 22(10), 1232-1238. https://doi.org/10.1093/bioinformatics/btl071

Prediction of HLA-DQ3.2β ligands : Evidence of multiple registers in class II binding peptides. / Tong, Joo Chuan; Zhang, Guang Lan; Tan, Tin Wee; August, J. Thomas; Brusic, Vladimir; Ranganathan, Shoba.

In: Bioinformatics, Vol. 22, No. 10, 15.05.2006, p. 1232-1238.

Research output: Contribution to journalArticle

Tong, JC, Zhang, GL, Tan, TW, August, JT, Brusic, V & Ranganathan, S 2006, 'Prediction of HLA-DQ3.2β ligands: Evidence of multiple registers in class II binding peptides', Bioinformatics, vol. 22, no. 10, pp. 1232-1238. https://doi.org/10.1093/bioinformatics/btl071
Tong, Joo Chuan ; Zhang, Guang Lan ; Tan, Tin Wee ; August, J. Thomas ; Brusic, Vladimir ; Ranganathan, Shoba. / Prediction of HLA-DQ3.2β ligands : Evidence of multiple registers in class II binding peptides. In: Bioinformatics. 2006 ; Vol. 22, No. 10. pp. 1232-1238.
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