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Improved methods for predicting peptide binding affinity to MHC class II molecules.

Authors :
Jensen, Kamilla Kjærgaard
Andreatta, Massimo
Marcatili, Paolo
Buus, Søren
Greenbaum, Jason A.
Yan, Zhen
Sette, Alessandro
Peters, Bjoern
Nielsen, Morten
Source :
Immunology; Jul2018, Vol. 154 Issue 3, p394-406, 13p
Publication Year :
2018

Abstract

Summary: Major histocompatibility complex class II (MHC‐II) molecules are expressed on the surface of professional antigen‐presenting cells where they display peptides to T helper cells, which orchestrate the onset and outcome of many host immune responses. Understanding which peptides will be presented by the MHC‐II molecule is therefore important for understanding the activation of T helper cells and can be used to identify T‐cell epitopes. We here present updated versions of two MHC–II–peptide binding affinity prediction methods, NetMHCII and NetMHCIIpan. These were constructed using an extended data set of quantitative MHC–peptide binding affinity data obtained from the Immune Epitope Database covering HLA‐DR, HLA‐DQ, HLA‐DP and H‐2 mouse molecules. We show that training with this extended data set improved the performance for peptide binding predictions for both methods. Both methods are publicly available at www.cbs.dtu.dk/services/NetMHCII-2.3 and www.cbs.dtu.dk/services/NetMHCIIpan-3.2. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00192805
Volume :
154
Issue :
3
Database :
Complementary Index
Journal :
Immunology
Publication Type :
Academic Journal
Accession number :
130168928
Full Text :
https://doi.org/10.1111/imm.12889