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1.
Ann Med Surg (Lond) ; 86(6): 3337-3348, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38846818

ABSTRACT

Objective: This study aims to elucidate anti-liver cancer components and potential mechanisms of Curcumae Rhizoma and Hedyotis diffusa Willd (CR-HDW). Methods: Effective components and targets of CR-HDW were identified from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Liver cancer-related genes were collected from GeneCards, Gene-Disease Association (DisGeNET), and National Center for Biotechnology Information (NCBI). Protein-protein interaction networks, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were conducted to analyze the identified genes. Molecular docking was used to simulate binding of the active components and their target proteins. Cell activity assay, western blot, and senescence-associated ß-galactosidase (SA-ß-gal) experiments were conducted to validate core targets identified from molecular docking. Results: Ten active compounds of CR-HDW were identified including quercetin, 3-epioleanic acid and hederagenin. The primary core proteins comprised Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), Protein Kinase B(AKT1), etc. The pathways for Phosphoinositide 3-kinase (PI3K)/ AKT, cellular senescence, Fork head boxO (FOXO) were revealed as important for anti-cancer activity of CR-HDW. Molecular docking demonstrated strong binding between liver cancer target proteins and major active components of CR-HDW. In-vitro experiments confirmed that hederagenin and 3-epioleolic acid inhibited HuH-7 cell growth, reduced expression of PI3K, AKT, and mechanistic target of rapamycin (mTOR) proteins. Hederagenin also induced HuH-7 senescence. Conclusions: In summary, The authors' results suggest that the CR-HDW component (Hederagenin, 3-epoxy-olanolic acid) can inhibit the proliferation of HuH-7 cells by decreasing PI3K, AKT, and mTOR. Hederagenin also induced HuH-7 senescence.

2.
Medicine (Baltimore) ; 101(47): e31969, 2022 Nov 25.
Article in English | MEDLINE | ID: mdl-36451386

ABSTRACT

To explore the mechanism of Epimedii Folium (HF) and Notoginseng Radix (NR) intervention in vascular dementia (VD). This study used the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database to collect the active ingredients and potential drug targets of HF and NR, the Uniprot database to convert drug target names into gene names, GeneCards, Drugbank, Therapeutic Target Database, and Online Mendelian Inheritance in Man database to collect the potential disease targets of VD, and then combined them with the drug targets to construct the HF-NR-VD protein-protein interaction (PPI) network by Search Tool for the Retrieval of Interacting (STRING). Cytoscape (version 3.7.1) was used to perform cluster analysis of the PPI network. Metascape database was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The potential interaction of the main components of the HF-NR couplet medicine with core disease targets was revealed by molecular docking simulations. There were 23 predicted active ingredients in HF and NR, and 109 common drug targets that may be involved in the treatment of VD. Through PPI network analysis, 30 proteins were identified as core proteins owing to their topological importance. GO functional analysis revealed that the primary biological processes were mainly related to inflammation, apoptosis, and the response to oxidative stress. KEGG pathway enrichment analysis revealed that TNF and PI3K/Akt signaling pathways may occupy the core status in the anti-VD system. Molecular docking results confirmed that the core targets of VD had a high affinity for the main compounds of the HF-NR couplet medicine. We demonstrated the multi-component, multi-target, and multi-pathway characteristics of HF-NR couplet medicine for the treatment of VD and provided a foundation for further clinical application and experimental research.


Subject(s)
Dementia, Vascular , Humans , Dementia, Vascular/drug therapy , Molecular Docking Simulation , Network Pharmacology , Phosphatidylinositol 3-Kinases , Databases, Genetic
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