Verification of the Potential Targets of the Herbal Prescription Sochehwan for Drug Repurposing Processes as Deduced by Network Pharmacology
Network pharmacology (NP) is a useful, emerging means of understanding the complex pharmacological mechanisms of traditional herbal medicines. Sochehwan (SCH) is a candidate herbal prescription for drug repurposing as it has been suggested to have beneficial effects on metabolic syndrome. In this st...
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oai:doaj.org-article:a6f35f9c073443449b98d5085c6665dd2021-11-25T18:51:38ZVerification of the Potential Targets of the Herbal Prescription Sochehwan for Drug Repurposing Processes as Deduced by Network Pharmacology10.3390/pr91120342227-9717https://doaj.org/article/a6f35f9c073443449b98d5085c6665dd2021-11-01T00:00:00Zhttps://www.mdpi.com/2227-9717/9/11/2034https://doaj.org/toc/2227-9717Network pharmacology (NP) is a useful, emerging means of understanding the complex pharmacological mechanisms of traditional herbal medicines. Sochehwan (SCH) is a candidate herbal prescription for drug repurposing as it has been suggested to have beneficial effects on metabolic syndrome. In this study, NP was adopted to complement the shortcomings of literature-based drug repurposing strategies in traditional herbal medicine. We conducted in vitro studies to confirm the effects of SCH on potential pharmacological targets identified by NP analysis. Herbal compounds and molecular targets of SCH were explored and screened from a traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) and an oriental medicine advanced searching integrated system (OASIS). Forty-seven key targets selected from a protein-protein interaction (PPI) network were analyzed with gene ontology (GO) term enrichment and KEGG pathway enrichment analysis to identify relevant categories. The tumor necrosis factor (TNF) and mitogen-activated protein kinase (MAPK) signaling pathways were presented as significant signaling pathways with lowest <i>p</i>-values by NP analysis, which were downregulated by SCH treatment. The signal transducer and activator of transcription 3 (STAT3) was identified as a core key target by NP analysis, and its phosphorylation ratio was confirmed to be significantly suppressed by SCH. In conclusion, the NP-based approach used for target prediction and experimental data obtained from Raw 264.7 cells strongly suggested that SCH can attenuate inflammatory status by modulating the phosphorylation status of STAT3.Dong-Woo LimDa-Hoon KimGa-Ram YuWon-Hwan ParkJai-Eun KimMDPI AGarticlenetwork pharmacologydrug repurposingkey target validationSochehwanGO enrichment analysisChemical technologyTP1-1185ChemistryQD1-999ENProcesses, Vol 9, Iss 2034, p 2034 (2021) |
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network pharmacology drug repurposing key target validation Sochehwan GO enrichment analysis Chemical technology TP1-1185 Chemistry QD1-999 |
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network pharmacology drug repurposing key target validation Sochehwan GO enrichment analysis Chemical technology TP1-1185 Chemistry QD1-999 Dong-Woo Lim Da-Hoon Kim Ga-Ram Yu Won-Hwan Park Jai-Eun Kim Verification of the Potential Targets of the Herbal Prescription Sochehwan for Drug Repurposing Processes as Deduced by Network Pharmacology |
description |
Network pharmacology (NP) is a useful, emerging means of understanding the complex pharmacological mechanisms of traditional herbal medicines. Sochehwan (SCH) is a candidate herbal prescription for drug repurposing as it has been suggested to have beneficial effects on metabolic syndrome. In this study, NP was adopted to complement the shortcomings of literature-based drug repurposing strategies in traditional herbal medicine. We conducted in vitro studies to confirm the effects of SCH on potential pharmacological targets identified by NP analysis. Herbal compounds and molecular targets of SCH were explored and screened from a traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) and an oriental medicine advanced searching integrated system (OASIS). Forty-seven key targets selected from a protein-protein interaction (PPI) network were analyzed with gene ontology (GO) term enrichment and KEGG pathway enrichment analysis to identify relevant categories. The tumor necrosis factor (TNF) and mitogen-activated protein kinase (MAPK) signaling pathways were presented as significant signaling pathways with lowest <i>p</i>-values by NP analysis, which were downregulated by SCH treatment. The signal transducer and activator of transcription 3 (STAT3) was identified as a core key target by NP analysis, and its phosphorylation ratio was confirmed to be significantly suppressed by SCH. In conclusion, the NP-based approach used for target prediction and experimental data obtained from Raw 264.7 cells strongly suggested that SCH can attenuate inflammatory status by modulating the phosphorylation status of STAT3. |
format |
article |
author |
Dong-Woo Lim Da-Hoon Kim Ga-Ram Yu Won-Hwan Park Jai-Eun Kim |
author_facet |
Dong-Woo Lim Da-Hoon Kim Ga-Ram Yu Won-Hwan Park Jai-Eun Kim |
author_sort |
Dong-Woo Lim |
title |
Verification of the Potential Targets of the Herbal Prescription Sochehwan for Drug Repurposing Processes as Deduced by Network Pharmacology |
title_short |
Verification of the Potential Targets of the Herbal Prescription Sochehwan for Drug Repurposing Processes as Deduced by Network Pharmacology |
title_full |
Verification of the Potential Targets of the Herbal Prescription Sochehwan for Drug Repurposing Processes as Deduced by Network Pharmacology |
title_fullStr |
Verification of the Potential Targets of the Herbal Prescription Sochehwan for Drug Repurposing Processes as Deduced by Network Pharmacology |
title_full_unstemmed |
Verification of the Potential Targets of the Herbal Prescription Sochehwan for Drug Repurposing Processes as Deduced by Network Pharmacology |
title_sort |
verification of the potential targets of the herbal prescription sochehwan for drug repurposing processes as deduced by network pharmacology |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/a6f35f9c073443449b98d5085c6665dd |
work_keys_str_mv |
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1718410666510909440 |