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NetMHCIIpan- 3. 0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ.

Authors :
Karosiene, Edita
Rasmussen, Michael
Blicher, Thomas
Lund, Ole
Buus, Søren
Nielsen, Morten
Source :
Immunogenetics; Oct2013, Vol. 65 Issue 10, p711-724, 14p
Publication Year :
2013

Abstract

Major histocompatibility complex class II (MHCII) molecules play an important role in cell-mediated immunity. They present specific peptides derived from endosomal proteins for recognition by T helper cells. The identification of peptides that bind to MHCII molecules is therefore of great importance for understanding the nature of immune responses and identifying T cell epitopes for the design of new vaccines and immunotherapies. Given the large number of MHC variants, and the costly experimental procedures needed to evaluate individual peptide-MHC interactions, computational predictions have become particularly attractive as first-line methods in epitope discovery. However, only a few so-called pan-specific prediction methods capable of predicting binding to any MHC molecule with known protein sequence are currently available, and all of them are limited to HLA-DR. Here, we present the first pan-specific method capable of predicting peptide binding to any HLA class II molecule with a defined protein sequence. The method employs a strategy common for HLA-DR, HLA-DP and HLA-DQ molecules to define the peptide-binding MHC environment in terms of a pseudo sequence. This strategy allows the inclusion of new molecules even from other species. The method was evaluated in several benchmarks and demonstrates a significant improvement over molecule-specific methods as well as the ability to predict peptide binding of previously uncharacterised MHCII molecules. To the best of our knowledge, the NetMHCIIpan- 3. 0 method is the first pan-specific predictor covering all HLA class II molecules with known sequences including HLA-DR, HLA-DP, and HLA-DQ. The NetMHCpan- 3. 0 method is available at . [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00937711
Volume :
65
Issue :
10
Database :
Complementary Index
Journal :
Immunogenetics
Publication Type :
Academic Journal
Accession number :
90245867
Full Text :
https://doi.org/10.1007/s00251-013-0720-y