Search

[Objectives] This study was conducted to explore the action mechanism of chemical components from stems of Isodon suzhouensis on prostate cancer based on UPLC-Q-TOF-MS/MS technique, network pharmacology, and molecular docking validation. #Methods] UPLC-Q-TOF-MS/MS was applied to search active components in stems of I. suzhouensis, and SwissTargetPrediction and PharmaMapper databases were used to predict their potential targets. The GeneCards database was adopted to screen the targets of prostate cancer, and the targets of the active components and the targets of prostate cancer were intersected to obtain common targets. A protein-protein interaction network was constructed, and also, an "active component-target-disease-pathway" network was constructed using Metascape for gene ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Moreover, AutoDock was adopted to perform molecular docking verification on key active components and core targets. #Results] Sixty three active components were screened from stems of I. suzhouensis, and they had 233 common targets with prostate cancer, mainly involving biological processes such as protein phosphorylation, response to hormones, active regulation of cell movement, cell response to lipids, and response to oxidative stress, as well as pathways in cancer, prostate cancer, micro ribonucleic acids in cancer, p53 signaling pathway, NF-KB signaling pathway and other signaling pathways, exerting anti-tumor effects. Molecular docking showed that the top 5 key active components had good binding ability with the top 5 core targets. [Conclusions] Active components from stems of I suzhouensis can exert therapeutic effects on prostate cancer through multiple targets and pathways. [ABSTRACT FROM AUTHOR]

[Objectives] Based on UPLC-Q-TOF-MS/MS, network pharmacology and molecular docking techniques, the mechanism of Euphorbia peplus in the treatment of Alzheimer's disease (AD) was studied. [Methods] The UPLC-Q-TOF-MS/MS technique was used to rapidly analyze the chemical components of E. peplus. Active components and potential targets of E. peplus were retrieved from TCMSP and Swiss Target Prediction database, and AD targets were screened using GeneCards database. The targets of E. peplus in the treatment of AD were obtained. The PPI network was constructed using String platform, and the network topology of Cytoscape software was used to compute and screen key targets, and the GO and KEGG pathway enrichment analysis was carried out in Metascape database to construct the "component-target-pathway-disease" network. Molecular docking was used to predict the binding properties of active ingredients and targets. [Results] The results of UPLC-Q-TOF-MS/MS showed that 83 compounds were identified from E. peplus, including 19 terpenoids, 10 phenolic acids and phenols, 16 flavonoids, 2 phenylpropanoids, 4 coumarins, 1 alkaloid, 1 anthraquinone and 30 other compounds. The results of network pharmacological analysis showed that 82 active ingredients were screened, and 279 common targets were identified for the treatment of AD, among which the key targets were ALB (albumin), GAPDH (glyceraldehyde triphosphate dehydrogenase), TNF (tumor necrosis factor), AKT1 (serine/threonine protein kinase 1), and IL6 (interleukin-6). KEGG enrichment analysis showed that key signaling pathways include cancer pathways, lipid and atherosclerosis, Alzheimer's disease, insulin resistance, serotonergic synapses, calcium signaling pathway, cAMP signaling pathway and other signaling pathways. Molecular docking results showed that 14-deoxyandrographolide, dehydroan-drographolide, licochalcone B, apigenin and naringenin may be the key components of E. peplus in the treatment of AD. [Conclusions] The results suggest that E. peplus can be used to treat Alzheimer's disease through multi-component, multi-target and multi-pathway. [ABSTRACT FROM AUTHOR]