scholarly journals Identification of polycystic ovary syndrome potential drug targets based on pathobiological similarity in the protein-protein interaction network

Oncotarget ◽  
2016 ◽  
Vol 7 (25) ◽  
pp. 37906-37919 ◽  
Author(s):  
Hao Huang ◽  
Yuehan He ◽  
Wan Li ◽  
Wenqing Wei ◽  
Yiran Li ◽  
...  
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Protein Interaction Network ◽  
Drug Targets ◽  
Polycystic Ovary ◽  
Interaction Network ◽  
Potential Drug ◽  
Ovary Syndrome ◽  
Protein Protein Interaction ◽  
Potential Drug Targets ◽  
Protein Protein Interaction Network

scholarly journals Control Analysis of Protein-Protein Interaction Network Reveals Potential Regulatory Targets for MYCN

2021 ◽  
Vol 11 ◽  
Author(s):  
Chunyu Pan ◽  
Yuyan Zhu ◽  
Meng Yu ◽  
Yongkang Zhao ◽  
Changsheng Zhang ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Protein Interaction Network ◽  
Regulatory Network ◽  
Interaction Network ◽  
Control Analysis ◽  
Potential Drug ◽  
Driver Genes ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network ◽  
Network Controllability

BackgroundMYCN is an oncogenic transcription factor of the MYC family and plays an important role in the formation of tissues and organs during development before birth. Due to the difficulty in drugging MYCN directly, revealing the molecules in MYCN regulatory networks will help to identify effective therapeutic targets.MethodsWe utilized network controllability theory, a recent developed powerful tool, to identify the potential drug target around MYCN based on Protein-Protein interaction network of MYCN. First, we constructed a Protein-Protein interaction network of MYCN based on public databases. Second, network control analysis was applied on network to identify driver genes and indispensable genes of the MYCN regulatory network. Finally, we developed a novel integrated approach to identify potential drug targets for regulating the function of the MYCN regulatory network.ResultsWe constructed an MYCN regulatory network that has 79 genes and 129 interactions. Based on network controllability theory, we analyzed driver genes which capable to fully control the network. We found 10 indispensable genes whose alternation will significantly change the regulatory pathways of the MYCN network. We evaluated the stability and correlation analysis of these genes and found EGFR may be the potential drug target which closely associated with MYCN.ConclusionTogether, our findings indicate that EGFR plays an important role in the regulatory network and pathways of MYCN and therefore may represent an attractive therapeutic target for cancer treatment.

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