Probing protein interaction networks by combining MS-based proteomics and structural data integration.
Fiche publication
Date publication
avril 2020
Journal
Journal of proteome research
Auteurs
Membres identifiés du Cancéropôle Est :
Dr CIANFERANI Sarah
Tous les auteurs :
Postic G, Marcoux J, Reys V, Andreani J, VandenBrouck Y, Bousquet MP, Mouton-Barbosa E, Cianférani S, Burlet-Schiltz O, Guerois R, Labesse G, Tuffery P
Lien Pubmed
Résumé
Protein-protein interactions play a major role in the molecular machinery of life and various techniques such as AP-MS are dedicated to their identification. However, those techniques return lists of proteins devoid of organizational structure, not detailing which proteins interact with which others. Proposing a hierarchical view of the interactions between the members of the flat list can be/become highly tedious for large datasets when done by hand. To help hierarchize this data, we introduce a new bioinformatics protocol that integrates information of the multimeric protein 3D structures available in the Protein Data Bank using remote homology detection, as well as information related to Short Linear Motifs and interaction data from the BioGrid. We illustrate on two unrelated use-cases of different complexity how our approach can be useful to decipher the network of interactions hidden in the list of input proteins, and how it provides added value compared to state-of-the-art resources such as Interactome3D or STRING. Particularly, we show the added value of using homology detection to distinguish between orthologs and paralogs, and to distinguish between core obligate and more facultative interactions. We also demonstrate the potential of considering interactions occurring through Short Linear Motifs.
Référence
J. Proteome Res.. 2020 Apr 27;: