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MoonDB 2.0: an updated database of extreme multifunctional and moonlighting proteins.
Ribeiro, Diogo M; Briere, Galadriel; Bely, Benoit; Spinelli, Lionel; Brun, Christine.
Afiliación
  • Ribeiro DM; Aix-Marseille Univ, INSERM, TAGC, UMR_S1090, Marseille, France.
  • Briere G; Aix-Marseille Univ, INSERM, TAGC, UMR_S1090, Marseille, France.
  • Bely B; The European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus CB10 1SD, UK.
  • Spinelli L; Aix-Marseille Univ, INSERM, TAGC, UMR_S1090, Marseille, France.
  • Brun C; Aix-Marseille Univ, INSERM, TAGC, UMR_S1090, Marseille, France.
Nucleic Acids Res ; 47(D1): D398-D402, 2019 01 08.
Article en En | MEDLINE | ID: mdl-30371819
MoonDB 2.0 (http://moondb.hb.univ-amu.fr/) is a database of predicted and manually curated extreme multifunctional (EMF) and moonlighting proteins, i.e. proteins that perform multiple unrelated functions. We have previously shown that such proteins can be predicted through the analysis of their molecular interaction subnetworks, their functional annotations and their association to distinct groups of proteins that are involved in unrelated functions. In MoonDB 2.0, we updated the set of human EMF proteins (238 proteins), using the latest functional annotations and protein-protein interaction networks. Furthermore, for the first time, we applied our method to four additional model organisms - mouse, fly, worm and yeast - and identified 54 novel EMF proteins in these species. In addition to novel predictions, this update contains 63 human and yeast proteins that were manually curated from literature, including descriptions of moonlighting functions and associated references. Importantly, MoonDB's interface was fully redesigned and improved, and its entries are now cross-referenced in the UniProt Knowledgebase (UniProtKB). MoonDB will be updated once a year with the novel EMF candidates calculated from the latest available protein interactions and functional annotations.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bases de Datos de Proteínas Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Nucleic Acids Res Año: 2019 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Bases de Datos de Proteínas Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Nucleic Acids Res Año: 2019 Tipo del documento: Article País de afiliación: Francia Pais de publicación: Reino Unido