Graph theoretic network analysis reveals protein pathways underlying cell death following neurotropic viral infection

被引:6
作者
Ghosh, Sourish [1 ]
Kumar, G. Vinodh [1 ]
Basu, Anirban [1 ]
Banerjee, Arpan [1 ]
机构
[1] Natl Brain Res Ctr, Gurgaon 122051, Haryana, India
来源
SCIENTIFIC REPORTS | 2015年 / 5卷
关键词
CHANDIPURA VIRUS; FACTOR-ALPHA; CROSS-TALK; APOPTOSIS; ENCEPHALITIS; INTERACTOME; ACTIVATION; DATABASE;
D O I
10.1038/srep14438
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Complex protein networks underlie any cellular function. Certain proteins play a pivotal role in many network configurations, disruption of whose expression proves fatal to the cell. An efficient method to tease out such key proteins in a network is still unavailable. Here, we used graph-theoretic measures on protein-protein interaction data (interactome) to extract biophysically relevant information about individual protein regulation and network properties such as formation of function specific modules (sub-networks) of proteins. We took 5 major proteins that are involved in neuronal apoptosis post Chandipura Virus (CHPV) infection as seed proteins in a database to create a meta-network of immediately interacting proteins (1st order network). Graph theoretic measures were employed to rank the proteins in terms of their connectivity and the degree upto which they can be organized into smaller modules (hubs). We repeated the analysis on 2nd order interactome that includes proteins connected directly with proteins of 1st order. FADD and Casp-3 were connected maximally to other proteins in both analyses, thus indicating their importance in neuronal apoptosis. Thus, our analysis provides a blueprint for the detection and validation of protein networks disrupted by viral infections.
引用
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页数:12
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