Bioinformatics Advance Access originally published online on March 1, 2006
Bioinformatics 2006 22(10):1232-1238; doi:10.1093/bioinformatics/btl071
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Prediction of HLA-DQ3.2ß Ligands: evidence of multiple registers in class II binding peptides
1 Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore 8 Medical Drive, Singapore 117597, Singapore
2 Institute for Infocomm Research 21 Heng Mui Keng Terrace, Singapore 119613, Singapore
3 Division of Biomedical Sciences, John Hopkins Medicine in Singapore 41 Science Park Road, Lobby C, The Gemini, Singapore 117610, Singapore
4 Department of Pharmacology and Molecular Sciences, John Hopkins University School of Medicine Baltimore, MD, USA
5 Australian Centre for Plant Functional Genomics, School of Land and Food Sciences, and Institute for Molecular Bioscience, The University of Queensland Brisbane 4072, Australia
6 Department of Chemistry and Biomolecular Sciences and Biotechnology Research Institute, Macquarie University NSW 2109, Australia
*To whom correspondence should be addressed.
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-DQ3.2ß complexes. We have developed a rapid and accurate protocol for docking candidate peptides into the DQ3.2ß receptor and a scoring function to discriminate binders from the background. The scoring function was rigorously trained, tested and validated using experimentally verified DQ3.2ß binding and non-binding peptides obtained from biochemical and functional studies.
Results: Our model predicts DQ3.2ß 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 DQ3.2ß 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.
Contact: shoba{at}els.mq.edu.au
Supplementary information: Supplementary data is available at Bioinformatics online.
Received on October 17, 2005; revised on February 22, 2006; accepted on February 23, 2006
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