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Biological interacting units identified in human protein networks reveal tissue-functional diversification and its impact on disease.
García-Vaquero, Marina L; Gama-Carvalho, Margarida; Pinto, Francisco R; De Las Rivas, Javier.
Afiliação
  • García-Vaquero ML; University of Lisboa, Faculty of Sciences, BioISI - Biosystems & Integrative Sciences Institute, Campo Grande, C8 bdg, Lisboa 1749-016, Portugal.
  • Gama-Carvalho M; Cancer Research Center (CiC-IBMCC, CSIC/USAL and IBSAL), Consejo Superior de Investigaciones Científicas (CSIC), University of Salamanca (USAL) and Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca 37007, Spain.
  • Pinto FR; University of Lisboa, Faculty of Sciences, BioISI - Biosystems & Integrative Sciences Institute, Campo Grande, C8 bdg, Lisboa 1749-016, Portugal.
  • De Las Rivas J; University of Lisboa, Faculty of Sciences, BioISI - Biosystems & Integrative Sciences Institute, Campo Grande, C8 bdg, Lisboa 1749-016, Portugal.
Comput Struct Biotechnol J ; 20: 3764-3778, 2022.
Article em En | MEDLINE | ID: mdl-35891788
ABSTRACT
Protein-protein interactions (PPI) play an essential role in the biological processes that occur in the cell. Therefore, the dissection of PPI networks becomes decisive to model functional coordination and predict pathological de-regulation. Cellular networks are dynamic and proteins display varying roles depending on the tissue-interactomic context. Thus, the use of centrality measures in individual proteins fall short to dissect the functional properties of the cell. For this reason, there is a need for more comprehensive, relational, and context-specific ways to analyze the multiple actions of proteins in different cells and identify specific functional assemblies within global biomolecular networks. Under this framework, we define Biological Interacting units (BioInt-U) as groups of proteins that interact physically and are enriched in a common Gene Ontology. A search strategy was applied on 33 tissue-specific (TS) PPI networks to generate BioInt libraries associated with each particular human tissue. The cross-tissue comparison showed that housekeeping assemblies incorporate different proteins and exhibit distinct network properties depending on the tissue. Furthermore, disease genes (DGs) of tissue-associated pathologies preferentially accumulate in units in the expected tissues, which in turn were more central in the TS networks. Overall, the study reveals a tissue-specific functional diversification based on the identification of specific protein units and suggests vulnerabilities specific of each tissue network, which can be applied to refine protein-disease association methods.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Portugal

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Portugal