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

BACKGROUND: The 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...

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Autores principales: Wang, Hui, Liu, Jiaqin, He, Jinbiao, Huang, Dengxia, Xi, Yujiang, Xiao, Ting, Ouyang, Qian, Zhang, Shiwei, Wan, Siyan, Chen, Xudong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681910/
https://www.ncbi.nlm.nih.gov/pubmed/36440424
http://dx.doi.org/10.3389/fpsyt.2022.1063489
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author Wang, Hui
Liu, Jiaqin
He, Jinbiao
Huang, Dengxia
Xi, Yujiang
Xiao, Ting
Ouyang, Qian
Zhang, Shiwei
Wan, Siyan
Chen, Xudong
author_facet Wang, Hui
Liu, Jiaqin
He, Jinbiao
Huang, Dengxia
Xi, Yujiang
Xiao, Ting
Ouyang, Qian
Zhang, Shiwei
Wan, Siyan
Chen, Xudong
author_sort Wang, Hui
collection PubMed
description BACKGROUND: The 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 METHODS: Bioactive 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. RESULTS: A 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. CONCLUSION: This 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.
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spelling pubmed-96819102022-11-24 Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study Wang, Hui Liu, Jiaqin He, Jinbiao Huang, Dengxia Xi, Yujiang Xiao, Ting Ouyang, Qian Zhang, Shiwei Wan, Siyan Chen, Xudong Front Psychiatry Psychiatry BACKGROUND: The 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 METHODS: Bioactive 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. RESULTS: A 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. CONCLUSION: This 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. Frontiers Media S.A. 2022-11-09 /pmc/articles/PMC9681910/ /pubmed/36440424 http://dx.doi.org/10.3389/fpsyt.2022.1063489 Text en Copyright © 2022 Wang, Liu, He, Huang, Xi, Xiao, Ouyang, Zhang, Wan and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychiatry
Wang, Hui
Liu, Jiaqin
He, Jinbiao
Huang, Dengxia
Xi, Yujiang
Xiao, Ting
Ouyang, Qian
Zhang, Shiwei
Wan, Siyan
Chen, Xudong
Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study
title Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study
title_full Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study
title_fullStr Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study
title_full_unstemmed Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study
title_short Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study
title_sort potential mechanisms underlying the therapeutic roles of sinisan formula in depression: based on network pharmacology and molecular docking study
topic Psychiatry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681910/
https://www.ncbi.nlm.nih.gov/pubmed/36440424
http://dx.doi.org/10.3389/fpsyt.2022.1063489
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