Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.

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 c...

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Autores principales:	Morten Nielsen, Claus Lundegaard, Thomas Blicher, Bjoern Peters, Alessandro Sette, Sune Justesen, Søren Buus, Ole Lund
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2008
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/6a407ec0fd0045ad9623747fb679cebf
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spelling	oai:doaj.org-article:6a407ec0fd0045ad9623747fb679cebf2021-11-25T05:41:14ZQuantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.1553-734X1553-735810.1371/journal.pcbi.1000107https://doaj.org/article/6a407ec0fd0045ad9623747fb679cebf2008-07-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/18604266/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358CD4 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.Morten NielsenClaus LundegaardThomas BlicherBjoern PetersAlessandro SetteSune JustesenSøren BuusOle LundPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 4, Iss 7, p e1000107 (2008)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Morten Nielsen Claus Lundegaard Thomas Blicher Bjoern Peters Alessandro Sette Sune Justesen Søren Buus Ole Lund Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.
description	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.
format	article
author	Morten Nielsen Claus Lundegaard Thomas Blicher Bjoern Peters Alessandro Sette Sune Justesen Søren Buus Ole Lund
author_facet	Morten Nielsen Claus Lundegaard Thomas Blicher Bjoern Peters Alessandro Sette Sune Justesen Søren Buus Ole Lund
author_sort	Morten Nielsen
title	Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.
title_short	Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.
title_full	Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.
title_fullStr	Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.
title_full_unstemmed	Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.
title_sort	quantitative predictions of peptide binding to any hla-dr molecule of known sequence: netmhciipan.
publisher	Public Library of Science (PLoS)
publishDate	2008
url	https://doaj.org/article/6a407ec0fd0045ad9623747fb679cebf
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Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan.

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