Article ; Online: A network pharmacology-based approach to explore the active ingredients and molecular mechanism of Shen-Kui-Tong-Mai granules on a rat model with chronic heart failure.
The Journal of pharmacy and pharmacology
2023 Volume 75, Issue 6, Page(s) 764–783
Abstract: ... therapeutic mechanisms of Shen-Kui-Tong-Mai granule (SKTMG) in the treatment of heart failure.: Methods ...
Abstract | Objectives: This study aimed to comprehensively investigate the potential active components and therapeutic mechanisms of Shen-Kui-Tong-Mai granule (SKTMG) in the treatment of heart failure. Methods: Network pharmacology combined with ultra-high performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS), molecular docking, and in vivo validation was performed to identify the active components and the potential targets for SKTMG to improve chronic heart failure (CHF). Key findings: The network pharmacology identified 192 active compounds and 307 potential consensus targets for SKTMG. On the other hand, network analysis discovered 10 core target genes related to the MAPK signal pathway. These genes include AKT1, STAT3, MAPK1, P53, SRC, JUN, TNF, APP, MAPK8 and IL6. The molecular docking results revealed that the SKTMG components were luteolin, quercetin, astragaloside IV and kaempferol, which could bind AKT1, MAPK1, P53, JUN, TNF and MAPK8. Additionally, SKTMG inhibited phosphorylation of AKT, P38, P53 and c-JUN, and reduced TNF-α expression in CHF rats. Conclusions: The present results demonstrated that network pharmacology combined with UHPLC-MS/MS, molecular docking and in vivo validation can facilitate the identification of active components and the potential targets for SKTMG to improve CHF. |
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MeSH term(s) | Animals ; Rats ; Molecular Docking Simulation ; Network Pharmacology ; Tandem Mass Spectrometry ; Tumor Suppressor Protein p53 ; Chronic Disease ; Drugs, Chinese Herbal/pharmacology ; Heart Failure/drug therapy |
Chemical Substances | Tumor Suppressor Protein p53 ; Drugs, Chinese Herbal |
Language | English |
Publishing date | 2023-03-13 |
Publishing country | England |
Document type | Journal Article |
ZDB-ID | 3107-0 |
ISSN | 2042-7158 ; 0022-3573 ; 0373-1022 |
ISSN (online) | 2042-7158 |
ISSN | 0022-3573 ; 0373-1022 |
DOI | 10.1093/jpp/rgad009 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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