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Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.
- Source :
-
PLoS computational biology [PLoS Comput Biol] 2008 Jul 04; Vol. 4 (7), pp. e1000107. Date of Electronic Publication: 2008 Jul 04. - Publication Year :
- 2008
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Abstract
- CD4 positive T helper cells control many aspects of specific immunity. These cells are specific for peptides derived from protein antigens and presented by molecules of the extremely polymorphic major histocompatibility complex (MHC) class II system. The identification of peptides that bind to MHC class II molecules is therefore of pivotal importance for rational discovery of immune epitopes. HLA-DR is a prominent example of a human MHC class II. Here, we present a method, NetMHCIIpan, that allows for pan-specific predictions of peptide binding to any HLA-DR molecule of known sequence. The method is derived from a large compilation of quantitative HLA-DR binding events covering 14 of the more than 500 known HLA-DR alleles. Taking both peptide and HLA sequence information into account, the method can generalize and predict peptide binding also for HLA-DR molecules where experimental data is absent. Validation of the method includes identification of endogenously derived HLA class II ligands, cross-validation, leave-one-molecule-out, and binding motif identification for hitherto uncharacterized HLA-DR molecules. The validation shows that the method can successfully predict binding for HLA-DR molecules-even in the absence of specific data for the particular molecule in question. Moreover, when compared to TEPITOPE, currently the only other publicly available prediction method aiming at providing broad HLA-DR allelic coverage, NetMHCIIpan performs equivalently for alleles included in the training of TEPITOPE while outperforming TEPITOPE on novel alleles. We propose that the method can be used to identify those hitherto uncharacterized alleles, which should be addressed experimentally in future updates of the method to cover the polymorphism of HLA-DR most efficiently. We thus conclude that the presented method meets the challenge of keeping up with the MHC polymorphism discovery rate and that it can be used to sample the MHC "space," enabling a highly efficient iterative process for improving MHC class II binding predictions.
- Subjects :
- Algorithms
Alleles
Amino Acid Sequence physiology
Binding Sites genetics
Binding Sites immunology
Databases, Protein
HLA-DR Antigens genetics
HLA-DR Antigens immunology
Humans
Major Histocompatibility Complex genetics
Molecular Sequence Data
Predictive Value of Tests
Protein Binding immunology
Reproducibility of Results
Sequence Alignment
Sequence Analysis, Protein
HLA-DR Antigens metabolism
Protein Interaction Mapping methods
Subjects
Details
- Language :
- English
- ISSN :
- 1553-7358
- Volume :
- 4
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- PLoS computational biology
- Publication Type :
- Academic Journal
- Accession number :
- 18604266
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1000107