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The TriMet_DB: A Manually Curated Database of the Metabolic Proteins of Triticum aestivum

Mass-spectrometry-based wheat proteomics is challenging because the current interpretation of mass spectrometry data relies on public databases that are not exhaustive (UniProtKB/Swiss-Prot) or contain many redundant and poor or un-annotated entries (UniProtKB/TrEMBL). Here, we report the developmen...

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Detalles Bibliográficos
Autores principales: Cunsolo, Vincenzo, Di Francesco, Antonella, Pittalà, Maria Gaetana Giovanna, Saletti, Rosaria, Foti, Salvatore
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9781733/
https://www.ncbi.nlm.nih.gov/pubmed/36558536
http://dx.doi.org/10.3390/nu14245377
Descripción
Sumario:Mass-spectrometry-based wheat proteomics is challenging because the current interpretation of mass spectrometry data relies on public databases that are not exhaustive (UniProtKB/Swiss-Prot) or contain many redundant and poor or un-annotated entries (UniProtKB/TrEMBL). Here, we report the development of a manually curated database of the metabolic proteins of Triticum aestivum (hexaploid wheat), named TriMet_DB (Triticum aestivum Metabolic Proteins DataBase). The manually curated TriMet_DB was generated in FASTA format so that it can be read directly by programs used to interpret the mass spectrometry data. Furthermore, the complete list of entries included in the TriMet_DB is reported in a freely available resource, which includes for each protein the description, the gene code, the protein family, and the allergen name (if any). To evaluate its performance, the TriMet_DB was used to interpret the MS data acquired on the metabolic protein fraction extracted from the cultivar MEC of Triticum aestivum. Data are available via ProteomeXchange with identifier PXD037709.