A network pharmacology based study of regulation effects of the main active components in Honghua injection on cerebrovascular disease network / 中国药学杂志
Chinese Pharmaceutical Journal
;
(24): 1402-1407, 2015.
Article
Dans Chinois
| WPRIM
| ID: wpr-859595
ABSTRACT
OBJECTIVE:
To investigate the regulation effects of main active components in Honghua Injection on cerebrovascular disease network.METHODS:
Cerebrovascular disease network was constructed using genes from public database RGD based on the protein-protein interaction (PPI) relationship databases HPRD and BioGRID. Then targets of five main active components in Honghua injection was retrieved from PubMed. Component-target relationships were extracted and associated with PPI in cerebrovascular disease. Component-target network was constructed with Cytoscape 3.1.0. Network analysis technologies were applied to find critical targets, biological pathways and potential synergistic effects among components.RESULTS:
The component-target network contains 940 nodes and 2360 edges. MCODE analysis extracted 28 clusters in which 18 clusters had at least 3 nodes. There were 6 clusters with score ≥3, and they were further investigated using BinGO analysis. The results showed that the main biological processes included regulation of macromolecule biosynthetic and metabolic processes, neurogenesis, apoptosis, angiogenesis, immune-inflammation reaction, response to hypoxia stress. Our study also indicated that Hydroxysafflor yellow A and Quercetin may show their cerebrovascular-protective potential based on their synergistic anti-apoptosis effects.CONCLUSION:
From the view of molecular network, our study applied network pharmacology methods and technologies to reveal the multi-target, multi-pathway mode of action of Honghua injection on anti-cerebro-vascular disease effects, and the synergistic effects among Hydroxysafflor yellow A and quercetin.
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
langue:
Chinois
Texte intégral:
Chinese Pharmaceutical Journal
Année:
2015
Type:
Article
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