Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study

被引:16
作者
Wang, Hui [1 ,2 ]
Liu, Jiaqin [3 ,4 ]
He, Jinbiao [2 ]
Huang, Dengxia [2 ]
Xi, Yujiang [2 ]
Xiao, Ting [5 ]
Ouyang, Qian [6 ]
Zhang, Shiwei [2 ]
Wan, Siyan [2 ]
Chen, Xudong [1 ]
机构
[1] Cent South Univ, Xiangya Hosp 2, Natl Clin Res Ctr Mental Disorders, Dept Psychiat, Changsha, Peoples R China
[2] Yunnan Univ Tradit Chinese Med, Kunming, Peoples R China
[3] Cent South Univ, Xiangya Hosp 2, Dept Pharm, Changsha, Peoples R China
[4] Cent South Univ, Inst Clin Pharm, Changsha, Peoples R China
[5] Hunan Univ Chinese Med, Affiliated Hosp 1, Changsha, Peoples R China
[6] Hunan Univ Chinese Med, Changsha, Peoples R China
来源
FRONTIERS IN PSYCHIATRY | 2022年 / 13卷
基金
中国国家自然科学基金;
关键词
sinisan formula; depression; network pharmacology; molecular docking; neurotransmitter-related mechanisms; ANTIDEPRESSANTS; INVOLVEMENT; TRANSITION; SYSTEMS; RISK;
D O I
10.3389/fpsyt.2022.1063489
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
BackgroundThe incidence of depression has been increasing globally, which has brought a serious burden to society. Sinisan Formula (SNSF), a well-known formula of traditional Chinese medicine (TCM), has been found to demonstrate an antidepressant effect. However, the therapeutic mechanism of this formula remains unclear. Thus, the present study aimed to explore the mechanism of SNSF in depression through network pharmacology combined with molecular docking methods. Materials and methodsBioactive compounds, potential targets of SNSF, and related genes of depression were obtained from public databases. Essential ingredients, potential targets, and signaling pathways were identified using bioinformatics analysis, including protein-protein interaction (PPI), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, Autodock software was further performed for conducting molecular docking to verify the binding ability of active ingredients to targets. ResultsA total of 91 active compounds were successfully identified in SNSF with the use of the comprehensive network pharmacology approach, and they were found to be closely connected to 112 depression-related targets, among which CREB1, NOS3, CASP3, TP53, ESR1, and SLC6A4 might be the main potential targets for the treatment of depression. GO analysis revealed 801 biological processes, 123 molecular functions, and 67 cellular components. KEGG pathway enrichment analysis indicated that neuroactive ligand-receptor interaction, serotonergic synapse pathways, dopaminergic synapse pathways, and GABAergic synapse pathways might have played a role in treating depression. Molecular docking suggested that beta-sitosterol, nobiletin, and 7-methoxy-2-methyl isoflavone bound well to the main potential targets. ConclusionThis study comprehensively illuminated the active ingredients, potential targets, primary pharmacological effects, and relevant mechanism of the SNSF in the treatment of depression. SNSF might exert its antidepressant effects by regulating the signaling pathway of 5-hydroxytryptamine, dopamine, GABA, and neuroactive ligand receptor interactions. Still, more pharmacological experiments are needed for verification.
引用
收藏
页数:15
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