How to Predict Binding Specificity and Ligands for New MHC-II Alleles with MixMHC2pred

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Serval ID
serval:BIB_DF5EF8125792
Type
A part of a book
Publication sub-type
Chapter: chapter ou part
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Title
How to Predict Binding Specificity and Ligands for New MHC-II Alleles with MixMHC2pred
Title of the book
Methods in Molecular Biology
Author(s)
Racle Julien, Gfeller David
Publisher
Springer US
ISBN
9781071638736
9781071638743
ISSN
1064-3745
1940-6029
ISSN-L
1064-3745
Publication state
Published
Issued date
2024
Peer-reviewed
Oui
Volume
2809
Pages
215-235
Language
english
Abstract
MHC-II molecules are key mediators of antigen presentation in vertebrate species and bind to their ligands with high specificity. The very high polymorphism of MHC-II genes within species and the fast-evolving nature of these genes across species has resulted in tens of thousands of different alleles, with hundreds of new alleles being discovered yearly through large sequencing projects in different species. Here we describe how to use MixMHC2pred to predict the binding specificity of any MHC-II allele directly from its amino acid sequence. We then show how both MHC-II ligands and CD4 <sup>+</sup> T cell epitopes can be predicted in different species with our approach. MixMHC2pred is available at http://mixmhc2pred.gfellerlab.org/ .
Keywords
MHC-II, binding specificity, machine learning, MHC-II peptidomics, immunopeptidomics, HLA-II, binding motifs, MHC-II ligand prediction, class II epitopes, computational immunology
Pubmed
Create date
28/06/2024 8:27
Last modification date
24/07/2024 6:17
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