Investigation of the mechanism of Prunella vulgaris in treatment of papillary thyroid carcinoma based on network pharmacology integrated molecular docking and experimental verification.
To analyze the molecular mechanism of Prunella vulgaris L. (PV) in the treatment of papillary thyroid carcinoma (PTC) by using network pharmacology combined with molecular docking verification. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database was used to predict the main active components of PV, Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, PubChem, and Swiss Target Prediction databases were used to obtain the corresponding targets of all active components. Targets collected for PTC treatment through Gene Cards, Digest and Online Mendelian Inheritance in Man databases respectively. The Search Tool for the Retrieval of Interaction Gene/Protein database was used to obtain the interaction information between proteins, and the topology analysis and visualization were carried out through Cytoscape 3.7.2 software (https://cytoscape.org/). The R package cluster profiler was used for gene ontology and Kyoto encyclopedia of genes and genomes analysis. The "active ingredient-target-disease" network was constructed by using Cyto scape 3.7.2, and topological analysis was carried out to obtain the core compound. The molecular docking was processed by using Discovery Studio 2019 software, and the core target and active ingredient were verified. The inhibition rate was detected by CCK8 method. Western blot was used to detect the expression levels of kaempferol anti-PTC related pathway proteins. A total of 11 components and 83 corresponding targets in the component target network of PV, of which 6 were the core targets of PV in the treatment of PTC. It was showed that quercetin, luteolin, beta (β)-sitosterol, kaempferol may be the core components of PV in the treatment of PTC. vascular endothelial growth factor A, tumor protein p53, transcription factor AP-1, prostaglandin endoperoxidase 2, interleukin 6, and IL-1B may be important targets for the treatment of PTC. The main biological processes mainly including response to nutrient levels, response to xenobiotic stimulus, response to extracellular stimulus, external side of plasma membrane, membrane raft, membrane microdomain, serine hydrolase activity, serine-type endopeptidase activity, antioxidant activity, etc IL-17 signaling pathway, and PI3K-Akt signaling pathway may affect the recurrence and metastasis of PTC. Kaempferol may significantly reduce the activity of Papillary cells of human thyroid carcinoma bcpap cell lines cells compared with quercetin, luteolin, β-sitosterol. Kaempferol may reduce the protein expression levels of interleukin 6, vascular endothelial growth factor A, transcription factor AP-1, tumor protein p53, 1L-1B and prostaglandin endoperoxidase 2, respectively. PV has the characteristics of multi-components, multi-targets and multi- pathways in the treatment of PTC, which network pharmacology help to provides a theoretical basis for the screening of effective components of PV and further research.
Zhu X
，Li Y
，Wang X
，Huang Y
，Mao J
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Network pharmacology to explore the molecular mechanisms of Prunella vulgaris for treating thyroid cancer.
Thyroid cancer (TC) is the most common endocrine malignancy that has rapidly increased in global incidence. Prunella vulgaris (PV) has manifested therapeutic effects in patients with TC. We aimed to investigate its molecular mechanisms against TC and provide potential drug targets by using network pharmacology and molecular docking.
The ingredients of PV were retrieved from Traditional Chinese Medicine Systematic Pharmacology Database. TC-related gene sets were established using the GeneCard and OMIM databases. The establishment of the TC-PV target gene interaction network was accomplished using the STRING database. Cytoscape constructed networks for visualization. Protein-protein interaction, gene ontology and the biological pathway Kyoto encyclopedia of genes and genomes enrichment analyses were performed to discover the potential mechanism. Molecular docking technology was used to analyze the effective compounds from PV for treating TC.
11 active compounds and 192 target genes were screened from PV. 177 potential targets were obtained by intersecting PV and TC gene sets. Network pharmacological analysis showed that the PV active ingredients including Vulgaxanthin-I, quercetin, Morin, Stigmasterol, poriferasterol monoglucoside, Spinasterol, kaempferol, delphinidin, stigmast-7-enol, beta-sitosterol and luteolin showed better correlation with TC target genes such as JUN, AKT1, mitogen-activated protein kinase 1, IL-6 and RELA. The gene ontology and Kyoto encyclopedia of genes and genomes indicated that PV can act by regulating the host defense and response to oxidative stress immune response and several signaling pathways are closely associated with TC, such as the TNF and IL-17. Protein-protein interaction network identified 8 hub genes. The molecular docking was conducted on the most significant gene MYC. Eleven active compounds of PV can enter the active pocket of MYC, namely poriferasterol monoglucoside, stigmasterol, beta-sitosterol, vulgaxanthin-I, spinasterol, stigmast-7-enol, luteolin, delphinidin, morin, quercetin and kaempferol. Further analysis showed that oriferasterol monoglucoside, followed by tigmasterol, were the potential therapeutic compound identified in PV for the treatment of TC.
The network pharmacological strategy integrates molecular docking to unravel the molecular mechanism of PV. MYC is a promising drug target to reduce oxidative stress damage and potential anti-tumor effect. Oriferasterol monoglucoside and kaempferol were 2 bioactive compounds of PV to treat TC. This provides a basis to understand the mechanism of the anti-TC activity of PV.
Zhang Z
，Zhou J
，Guo R
，Zhou Q
，Wang L
，Xiang X
，Ge S
，Cui Z
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ResearchGate
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钛学术
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