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

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. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Hui Wang [verfasserIn] Jiaqin Liu [verfasserIn] Jinbiao He [verfasserIn] Dengxia Huang [verfasserIn] Yujiang Xi [verfasserIn] Ting Xiao [verfasserIn] Qian Ouyang [verfasserIn] Shiwei Zhang [verfasserIn] Siyan Wan [verfasserIn] Xudong Chen [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	sinisan formula depression network pharmacology molecular docking neurotransmitter-related mechanisms

Übergeordnetes Werk:	In: Frontiers in Psychiatry - Frontiers Media S.A., 2010, 13(2022)
Übergeordnetes Werk:	volume:13 ; year:2022

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fpsyt.2022.1063489

Katalog-ID:	DOAJ083631577

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520			\|a 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.
650		4	\|a sinisan formula
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allfields	10.3389/fpsyt.2022.1063489 doi (DE-627)DOAJ083631577 (DE-599)DOAJ2e91ab2ad0b54db19e42593b46a286fc DE-627 ger DE-627 rakwb eng RC435-571 Hui Wang verfasserin aut Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. sinisan formula depression network pharmacology molecular docking neurotransmitter-related mechanisms Psychiatry Hui Wang verfasserin aut Jiaqin Liu verfasserin aut Jiaqin Liu verfasserin aut Jinbiao He verfasserin aut Dengxia Huang verfasserin aut Yujiang Xi verfasserin aut Ting Xiao verfasserin aut Qian Ouyang verfasserin aut Shiwei Zhang verfasserin aut Siyan Wan verfasserin aut Xudong Chen verfasserin aut In Frontiers in Psychiatry Frontiers Media S.A., 2010 13(2022) (DE-627)631498796 (DE-600)2564218-2 16640640 nnns volume:13 year:2022 https://doi.org/10.3389/fpsyt.2022.1063489 kostenfrei https://doaj.org/article/2e91ab2ad0b54db19e42593b46a286fc kostenfrei https://www.frontiersin.org/articles/10.3389/fpsyt.2022.1063489/full kostenfrei https://doaj.org/toc/1664-0640 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
spelling	10.3389/fpsyt.2022.1063489 doi (DE-627)DOAJ083631577 (DE-599)DOAJ2e91ab2ad0b54db19e42593b46a286fc DE-627 ger DE-627 rakwb eng RC435-571 Hui Wang verfasserin aut Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. sinisan formula depression network pharmacology molecular docking neurotransmitter-related mechanisms Psychiatry Hui Wang verfasserin aut Jiaqin Liu verfasserin aut Jiaqin Liu verfasserin aut Jinbiao He verfasserin aut Dengxia Huang verfasserin aut Yujiang Xi verfasserin aut Ting Xiao verfasserin aut Qian Ouyang verfasserin aut Shiwei Zhang verfasserin aut Siyan Wan verfasserin aut Xudong Chen verfasserin aut In Frontiers in Psychiatry Frontiers Media S.A., 2010 13(2022) (DE-627)631498796 (DE-600)2564218-2 16640640 nnns volume:13 year:2022 https://doi.org/10.3389/fpsyt.2022.1063489 kostenfrei https://doaj.org/article/2e91ab2ad0b54db19e42593b46a286fc kostenfrei https://www.frontiersin.org/articles/10.3389/fpsyt.2022.1063489/full kostenfrei https://doaj.org/toc/1664-0640 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
allfields_unstemmed	10.3389/fpsyt.2022.1063489 doi (DE-627)DOAJ083631577 (DE-599)DOAJ2e91ab2ad0b54db19e42593b46a286fc DE-627 ger DE-627 rakwb eng RC435-571 Hui Wang verfasserin aut Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. sinisan formula depression network pharmacology molecular docking neurotransmitter-related mechanisms Psychiatry Hui Wang verfasserin aut Jiaqin Liu verfasserin aut Jiaqin Liu verfasserin aut Jinbiao He verfasserin aut Dengxia Huang verfasserin aut Yujiang Xi verfasserin aut Ting Xiao verfasserin aut Qian Ouyang verfasserin aut Shiwei Zhang verfasserin aut Siyan Wan verfasserin aut Xudong Chen verfasserin aut In Frontiers in Psychiatry Frontiers Media S.A., 2010 13(2022) (DE-627)631498796 (DE-600)2564218-2 16640640 nnns volume:13 year:2022 https://doi.org/10.3389/fpsyt.2022.1063489 kostenfrei https://doaj.org/article/2e91ab2ad0b54db19e42593b46a286fc kostenfrei https://www.frontiersin.org/articles/10.3389/fpsyt.2022.1063489/full kostenfrei https://doaj.org/toc/1664-0640 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
allfieldsGer	10.3389/fpsyt.2022.1063489 doi (DE-627)DOAJ083631577 (DE-599)DOAJ2e91ab2ad0b54db19e42593b46a286fc DE-627 ger DE-627 rakwb eng RC435-571 Hui Wang verfasserin aut Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. sinisan formula depression network pharmacology molecular docking neurotransmitter-related mechanisms Psychiatry Hui Wang verfasserin aut Jiaqin Liu verfasserin aut Jiaqin Liu verfasserin aut Jinbiao He verfasserin aut Dengxia Huang verfasserin aut Yujiang Xi verfasserin aut Ting Xiao verfasserin aut Qian Ouyang verfasserin aut Shiwei Zhang verfasserin aut Siyan Wan verfasserin aut Xudong Chen verfasserin aut In Frontiers in Psychiatry Frontiers Media S.A., 2010 13(2022) (DE-627)631498796 (DE-600)2564218-2 16640640 nnns volume:13 year:2022 https://doi.org/10.3389/fpsyt.2022.1063489 kostenfrei https://doaj.org/article/2e91ab2ad0b54db19e42593b46a286fc kostenfrei https://www.frontiersin.org/articles/10.3389/fpsyt.2022.1063489/full kostenfrei https://doaj.org/toc/1664-0640 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
allfieldsSound	10.3389/fpsyt.2022.1063489 doi (DE-627)DOAJ083631577 (DE-599)DOAJ2e91ab2ad0b54db19e42593b46a286fc DE-627 ger DE-627 rakwb eng RC435-571 Hui Wang verfasserin aut Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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. sinisan formula depression network pharmacology molecular docking neurotransmitter-related mechanisms Psychiatry Hui Wang verfasserin aut Jiaqin Liu verfasserin aut Jiaqin Liu verfasserin aut Jinbiao He verfasserin aut Dengxia Huang verfasserin aut Yujiang Xi verfasserin aut Ting Xiao verfasserin aut Qian Ouyang verfasserin aut Shiwei Zhang verfasserin aut Siyan Wan verfasserin aut Xudong Chen verfasserin aut In Frontiers in Psychiatry Frontiers Media S.A., 2010 13(2022) (DE-627)631498796 (DE-600)2564218-2 16640640 nnns volume:13 year:2022 https://doi.org/10.3389/fpsyt.2022.1063489 kostenfrei https://doaj.org/article/2e91ab2ad0b54db19e42593b46a286fc kostenfrei https://www.frontiersin.org/articles/10.3389/fpsyt.2022.1063489/full kostenfrei https://doaj.org/toc/1664-0640 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2022
language	English
source	In Frontiers in Psychiatry 13(2022) volume:13 year:2022
sourceStr	In Frontiers in Psychiatry 13(2022) volume:13 year:2022
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	sinisan formula depression network pharmacology molecular docking neurotransmitter-related mechanisms Psychiatry
isfreeaccess_bool	true
container_title	Frontiers in Psychiatry
authorswithroles_txt_mv	Hui Wang @@aut@@ Jiaqin Liu @@aut@@ Jinbiao He @@aut@@ Dengxia Huang @@aut@@ Yujiang Xi @@aut@@ Ting Xiao @@aut@@ Qian Ouyang @@aut@@ Shiwei Zhang @@aut@@ Siyan Wan @@aut@@ Xudong Chen @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	631498796
id	DOAJ083631577
language_de	englisch
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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. 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callnumber-first	R - Medicine
author	Hui Wang
spellingShingle	Hui Wang misc RC435-571 misc sinisan formula misc depression misc network pharmacology misc molecular docking misc neurotransmitter-related mechanisms misc Psychiatry Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study
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topic_title	RC435-571 Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study sinisan formula depression network pharmacology molecular docking neurotransmitter-related mechanisms
topic	misc RC435-571 misc sinisan formula misc depression misc network pharmacology misc molecular docking misc neurotransmitter-related mechanisms misc Psychiatry
topic_unstemmed	misc RC435-571 misc sinisan formula misc depression misc network pharmacology misc molecular docking misc neurotransmitter-related mechanisms misc Psychiatry
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title	Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study
ctrlnum	(DE-627)DOAJ083631577 (DE-599)DOAJ2e91ab2ad0b54db19e42593b46a286fc
title_full	Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study
author_sort	Hui Wang
journal	Frontiers in Psychiatry
journalStr	Frontiers in Psychiatry
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author_browse	Hui Wang Jiaqin Liu Jinbiao He Dengxia Huang Yujiang Xi Ting Xiao Qian Ouyang Shiwei Zhang Siyan Wan Xudong Chen
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title_sort	potential mechanisms underlying the therapeutic roles of sinisan formula in depression: based on network pharmacology and molecular docking study
callnumber	RC435-571
title_auth	Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study
abstract	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.
abstractGer	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.
abstract_unstemmed	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.
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title_short	Potential mechanisms underlying the therapeutic roles of sinisan formula in depression: Based on network pharmacology and molecular docking study
url	https://doi.org/10.3389/fpsyt.2022.1063489 https://doaj.org/article/2e91ab2ad0b54db19e42593b46a286fc https://www.frontiersin.org/articles/10.3389/fpsyt.2022.1063489/full https://doaj.org/toc/1664-0640
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author2	Hui Wang Jiaqin Liu Jinbiao He Dengxia Huang Yujiang Xi Ting Xiao Qian Ouyang Shiwei Zhang Siyan Wan Xudong Chen
author2Str	Hui Wang Jiaqin Liu Jinbiao He Dengxia Huang Yujiang Xi Ting Xiao Qian Ouyang Shiwei Zhang Siyan Wan Xudong Chen
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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). 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