Mechanism of Chaihu Shugan Powder () for Treating Depression Based on Network Pharmacology.
10.1007/s11655-019-3172-x
- Author:
Yuan-Yue LIU
1
;
Dan HU
2
;
Qi-Qi FAN
1
;
Xiao-Hao ZHANG
3
;
Yi-Cheng ZHU
1
;
Miao-Yan NI
1
;
Yan-Ming WANG
1
;
Lan-Kun ZHANG
2
;
Lei SHENG
4
Author Information
1. The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China.
2. Department of Neurology, Jiangsu Provincial Second Chinese Medicine Hospital, The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China.
3. Department of Neurology, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, China.
4. Department of Neurology, Jiangsu Provincial Second Chinese Medicine Hospital, The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China. hejieqong1234@163.com.
- Publication Type:Journal Article
- Keywords:
Chaihu Shugan Powder;
Chinese medicine;
depression;
network pharmacology;
pathway;
target
- From:
Chinese journal of integrative medicine
2020;26(12):921-928
- CountryChina
- Language:English
-
Abstract:
OBJECTIVE:To analyze the effective components of Chinese medicine (CM) contained in Chaihu Shugan Powder (, CSP) in the treatment of depressive disorders and to predict its anti-depressant mechanism by network pharmacology.
METHODS:Absorption, distribution, metabolism, excretion, and toxicity calculation method was used to screen the active components of CSP. Traditional Chinese Medicine System Pharmacological Database Analysis Platform and text mining tool (GoPuMed database) were used to predict and screen the active ingredients of CSP and anti-depressive targets. Through Genetic Association Database, Therapeutic Target Database, and PharmGkb database targets for depression were obtained. Cytoscape3.2.1 software was used to establish a network map of the active ingredients-targets of CSP, and to analyze gene function and metabolic pathways through Database for Annotation, Visualization and Integrated Discovery and the Omicshare database.
RESULTS:The 121 active ingredients and 15 depression-related targets which were screened from the database can exert antidepressant effects by improving the neural plasticity, growth, transfer condition and gene expression of neuronal cell, and the raise of the expression of gap junction protein. The 15 targets passed 14 metabolic pathways, mainly involved in the regulation of neurotransmitters (5-hydroxytryptamine, dopamine and epinephrine), inflammatory mediator regulation of TRP channels, calcium signaling pathway, cyclic adenosine monophosphate signaling pathway and neuroactive ligand-receptor interaction and other signal channels to exert anti-depressant effects.
CONCLUSION:This article reveals the possible mechanism of CSP in the treatment of depression through network pharmacology research, and lays a foundation for further target studies.
