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Apoptosis regulatory protein-protein interaction demonstrates hierarchical scale-free fractal network.
- Source :
-
Briefings in Bioinformatics . Aug2015, Vol. 16 Issue 4, p675-699. 25p. - Publication Year :
- 2015
-
Abstract
- Dysregulation or inhibition of apoptosis favors cancer and many other diseases. Understanding of the network interaction of the genes involved in apoptotic pathway, therefore, is essential, to look for targets of therapeutic intervention. Here we used the network theory methods, using experimentally validated 25 apoptosis regulatory proteins and identified important genes for apoptosis regulation, which demonstrated a hierarchical scale-free fractal protein-protein interaction network. TP53, BRCA1, UBIQ and CASP3 were recognized as a four key regulators. BRCA1 and UBIQ were also individually found to control highly clustered modules and play an important role in the stability of the overall network. The connection among the BRCA1, UBIQ and TP53 proteins was found to be important for regulation, which controlled their own respective communities and the overall network topology. The feedback loop regulation motif was identified among NPM1, BRCA1 and TP53, and these crucial motif topologies were also reflected in high frequency. The propagation of the perturbed signal from hubs was found to be active up to some distance, after which propagation started decreasing and TP53 was the most efficient signal propagator. From the functional enrichment analysis, most of the apoptosis regulatory genes associated with cardiovascular diseases and highly expressed in brain tissues were identified. Apart fromTP53, BRCA1 was observed to regulate apoptosis by influencing motif, propagation of signals and module regulation, reflecting their biological significance. In future, biochemical investigation of the observed hub-interacting partners could provide further understanding about their role in the pathophysiology of cancer. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14675463
- Volume :
- 16
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Briefings in Bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 109528571
- Full Text :
- https://doi.org/10.1093/bib/bbu036