Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification
Top Cited Papers
- 29 September 2015
- journal article
- research article
- Published by Springer Science and Business Media LLC in Immunogenetics
- Vol. 67 (11-12), 641-650
- https://doi.org/10.1007/s00251-015-0873-y
Abstract
A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented on the cell surface where it can be recognized by T helper lymphocytes. NetMHCIIpan is a state-of-the-art method for the quantitative prediction of peptide binding to any human or mouse MHC class II molecule of known sequence. In this paper, we describe an updated version of the method with improved peptide binding register identification. Binding register prediction is concerned with determining the minimal core region of nine residues directly in contact with the MHC binding cleft, a crucial piece of information both for the identification and design of CD4+ T cell antigens. When applied to a set of 51 crystal structures of peptide-MHC complexes with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped to the epitope binding core. NetMHCIIpan is publicly available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.1.Keywords
This publication has 40 references indexed in Scilit:
- TEPITOPEpan: Extending TEPITOPE for Peptide Binding Prediction Covering over 700 HLA-DR MoleculesPLOS ONE, 2012
- NNAlign: A Web-Based Prediction Method Allowing Non-Expert End-User Discovery of Sequence Motifs in Quantitative Peptide DataPLOS ONE, 2011
- NetMHCIIpan-2.0 - Improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedureImmunome Research, 2010
- NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding predictionBMC Bioinformatics, 2009
- Functional recombinant MHC class II molecules and high-throughput peptide-binding assaysImmunome Research, 2009
- Quantitative Predictions of Peptide Binding to Any HLA-DR Molecule of Known Sequence: NetMHCIIpanPLoS Computational Biology, 2008
- Amino Acid Similarity Accounts for T Cell Cross-Reactivity and for “Holes” in the T Cell RepertoirePLOS ONE, 2008
- NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known SequencePLOS ONE, 2007
- Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment methodBMC Bioinformatics, 2007
- Reliable prediction of T‐cell epitopes using neural networks with novel sequence representationsProtein Science, 2003