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Mechanism of Chaihu Shugan Powder () for Treating Depression Based on Network Pharmacology.
Liu, Yuan-Yue; Hu, Dan; Fan, Qi-Qi; Zhang, Xiao-Hao; Zhu, Yi-Cheng; Ni, Miao-Yan; Wang, Yan-Ming; Zhang, Lan-Kun; Sheng, Lei.
Afiliación
  • Liu YY; The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China.
  • Hu D; Department of Neurology, Jiangsu Provincial Second Chinese Medicine Hospital, The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China.
  • Fan QQ; The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China.
  • Zhang XH; Department of Neurology, Jinling Hospital, Medical School of Nanjing University, Nanjing, 210002, China.
  • Zhu YC; The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China.
  • Ni MY; The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China.
  • Wang YM; The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China.
  • Zhang LK; Department of Neurology, Jiangsu Provincial Second Chinese Medicine Hospital, The Second Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, 210017, China.
  • Sheng L; 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.
Chin J Integr Med ; 26(12): 921-928, 2020 Dec.
Article en En | MEDLINE | ID: mdl-31630361
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.
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Texto completo: 1 Bases de datos: MEDLINE Medicinas Tradicionales: Medicinas_tradicionales_de_asia / Medicina_china Métodos Terapéuticos y Terapias MTCI: Terapias_biologicas Asunto principal: Medicamentos Herbarios Chinos / Depresión / Antidepresivos Idioma: En Revista: Chin J Integr Med Año: 2020 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Medicinas Tradicionales: Medicinas_tradicionales_de_asia / Medicina_china Métodos Terapéuticos y Terapias MTCI: Terapias_biologicas Asunto principal: Medicamentos Herbarios Chinos / Depresión / Antidepresivos Idioma: En Revista: Chin J Integr Med Año: 2020 Tipo del documento: Article País de afiliación: China