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Network pharmacology based virtual screening of active constituents of Prunella vulgaris L. and the molecular mechanism against breast cancer.

ABSTRACT: Prunella vulgaris L, a perennial herb widely used in Asia in the treatment of various diseases including cancer. In vitro studies have demonstrated the therapeutic effect of Prunella vulgaris L. against breast cancer through multiple pathways. However, the nature of the biological mechanisms remains unclear. In this study, a Network pharmacology based approach was used to explore active constituents and potential molecular mechanisms of Prunella vulgaris L. for the treatment of breast cancer. The methods adopted included active constituents prescreening, target prediction, GO and KEGG pathway enrichment analysis. Molecular docking experiments were used to further validate network pharmacology results. The predicted results showed that there were 19 active ingredients in Prunella vulgaris L. and 31 potential gene targets including AKT1, EGFR, MYC, and VEGFA. Further, analysis of the potential biological mechanisms of Prunella vulgaris L. against breast cancer was performed by investigating the relationship between the active constituents, target genes and pathways. Network analysis showed that Prunella vulgaris L. exerted a promising preventive effect on breast cancer by acting on tumor-associated signaling pathways. This provides a basis to understand the mechanism of the anti-breast cancer activity of Prunella vulgaris L.

SUBMITTER: Zhang X

PROVIDER: S-EPMC7519149 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Network pharmacology based virtual screening of active constituents of Prunella vulgaris L. and the molecular mechanism against breast cancer.

Zhang Xiaobo X Shen Tao T Zhou Xin X Tang Xuehua X Gao Rui R Xu Lu L Wang Long L Zhou Zubin Z Lin Jingjing J Hu Yuanzhang Y

Scientific reports 20200925 1

Prunella vulgaris L, a perennial herb widely used in Asia in the treatment of various diseases including cancer. In vitro studies have demonstrated the therapeutic effect of Prunella vulgaris L. against breast cancer through multiple pathways. However, the nature of the biological mechanisms remains unclear. In this study, a Network pharmacology based approach was used to explore active constituents and potential molecular mechanisms of Prunella vulgaris L. for the treatment of breast cancer. Th ...[more]

PMID: 32978480

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Project description: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.

Project description:BackgroundPrunella vulgaris L. is effective in the treatment of breast cancer (BRCA); however, the underlying mechanism is still unclear. The aim of this study was to elucidate the mechanism of treatment of BRCA by P. vulgaris using network pharmacology and molecular docking technology, and to verify the experimental results using human BRCA MDA-MB-231 cells.MethodsActive components and action targets of P. vulgaris were determined using the TCMSP™, SwissTarget Prediction™, and TargetNet™ databases. GeneCards™ and OMIM™ provided BRCA targets. After obtaining common targets, a protein-protein interaction (PPI) network was constructed using the STRING™ database, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted using the Xiantao™ academic database. Cytoscape™ was used to construct "single drug-disease-component-target" and "single drug-disease-component-target-pathway" networks. The Human Protein Atlas™ was used to determine protein expression levels in BRCA cell lines. AutoDock tools™ were used to carry out molecular docking for the first 10 targets of quercetin and the PPI network. Finally, the abovementioned results were verified using cell experiments.ResultsWe obtained 11 active components, 198 targets, and 179 common targets, including DUOX2, MET, TOP2A, and ERBB3. The results of KEGG pathway analysis screened 188 related signaling pathways and indicated the potential key role of PI3K-Akt and MAPK signaling pathways in the antibreast cancer process of P. vulgaris. The results of molecular docking showed that the first 10 targets of quercetin interacted well with the protein network. Cell experiments showed that quercetin effectively inhibited the proliferation of MDA-MB-231 cells by regulating apoptosis and cell cycle, which may be partly related to the MAPK signaling pathway.ConclusionSynergistic effects of multiple components, targets, and pathways on the anti-BRCA activity of P. vulgaris could provide a theoretical basis for further study on its complex anti-BRCA mechanism.

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Network pharmacology based virtual screening of active constituents of Prunella vulgaris L. and the molecular mechanism against breast cancer.

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Network pharmacology based virtual screening of active constituents of Prunella vulgaris L. and the molecular mechanism against breast cancer.

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