Artículo
NNAlign-MA; MHC peptidome deconvolution for accurate MHC binding motif characterization and improved t-cell epitope predictions
Alvarez, Bruno
; Reynisson, Birkir; Barra, Carolina M
; Buus, Søren; Ternette, Nicola; Connelley, Tim; Andreatta, Massimo
; Nielsen, Morten
Fecha de publicación:
10/2019
Editorial:
American Society for Biochemistry and Molecular Biology
Revista:
Molecular & Cellular Proteomics
ISSN:
1535-9476
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The set of peptides presented on a cell´s surface by MHC molecules is known as the immunopeptidome. Current mass spectrometry technologies allow for identification of large peptidomes, and studies have proven these data to be a rich source of information for learning the rules of MHC-mediated antigen presentation. Immunopeptidomes are usually poly-specific, containing multiple sequence motifs matching the MHC molecules expressed in the system under investigation. Motif deconvolution -the process of associating each ligand to its presenting MHC molecule(s)- is therefore a critical and challenging step in the analysis of MS-eluted MHC ligand data. Here, we describe NNAlign_MA, a computational method designed to address this challenge and fully benefit from large, poly-specific data sets of MS-eluted ligands. NNAlign_MA simultaneously performs the tasks of i) clustering peptides into individual specificities; ii) automatic annotation of each cluster to an MHC molecule; and iii) training of a prediction model covering all MHCs present in the training set. NNAlign_MA was benchmarked on large and diverse datasets, covering class I and class II data. In all cases, the method was demonstrated to outperform state-of-the-art methods, effectively expanding the coverage of alleles for which accurate predictions can be made, resulting in improved identification of both eluted ligands and T cell epitopes. Given its high flexibility and ease of use, we expect NNAlign_MA to serve as an effective tool to increase our understanding of the rules of MHC antigen presentation and guide the development of novel T cell-based therapeutics.
Palabras clave:
MHC
,
Immunoinformatics
,
Mass Spectrometry
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Articulos (IIBIO)
Articulos de INSTITUTO DE INVESTIGACIONES BIOTECNOLOGICAS
Articulos de INSTITUTO DE INVESTIGACIONES BIOTECNOLOGICAS
Citación
Alvarez, Bruno; Reynisson, Birkir; Barra, Carolina M; Buus, Søren; Ternette, Nicola; et al.; NNAlign-MA; MHC peptidome deconvolution for accurate MHC binding motif characterization and improved t-cell epitope predictions; American Society for Biochemistry and Molecular Biology; Molecular & Cellular Proteomics; 18; 12; 10-2019; 2459-2477
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