Insights from systems pharmacology into cardiovascular drug discovery and therapy

BMC Systems Biology

Yonghua Wang¹  Ling Yang³  Aiping Lu²  Pidong Li¹  Xuetong Chen¹  Chunli Zheng¹  Jiangfeng Du⁴  Chao Huang¹  Jinlong Ru¹  Yingxue Fu¹  Peng Li¹ 

[1] Center of Bioinformatics, College of Life Science, Northwest A and F University, Yang ling 712100, Shaanxi, China;School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong;Lab of Pharmaceutical Resource Discovery, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning, China;Department of Biochemistry, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, the Netherlands

关键词: Gene-disease network;    Drug-target network;    Drug discovery;    Network analysis;    Network pharmacology;    Cardiovascular disease;   

Others  :  1091078
DOI  :  10.1186/s12918-014-0141-z

 received in 2014-07-25, accepted in 2014-12-11,  发布年份 2014

【 摘 要 】

Background

Given the complex nature of cardiovascular disease (CVD), information derived from a systems-level will allow us to fully interrogate features of CVD to better understand disease pathogenesis and to identify new drug targets.

Results

Here, we describe a systematic assessment of the multi-layer interactions underlying cardiovascular drugs, targets, genes and disorders to reveal comprehensive insights into cardiovascular systems biology and pharmacology. We have identified 206 effect-mediating drug targets, which are modulated by 254 unique drugs, of which, 43% display activities across different protein families (sequence similarity < 30%), highlighting the fact that multitarget therapy is suitable for CVD. Although there is little overlap between cardiovascular protein targets and disease genes, the two groups have similar pleiotropy and intimate relationships in the human disease gene-gene and cellular networks, supporting their similar characteristics in disease development and response to therapy. We also characterize the relationships between different cardiovascular disorders, which reveal that they share more etiological commonalities with each other rooted in the global disease-disease networks. Furthermore, the disease modular analysis demonstrates apparent molecular connection between 227 cardiovascular disease pairs.

Conclusions

All these provide important consensus as to the cause, prevention, and treatment of various CVD disorders from systems-level perspective.

【 授权许可】

   
2014 Li et al.; licensee BioMed Central.

【 图 表 】

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