Abstract

Clinacanthus nutans (for abbreviation thereafter) is often used as medicine in the form of fresh juice in the folk to treat many kinds of cancers, including renal cell carcinoma (RCC). It is speculated that its active ingredient may have heat sensitivity, but there are currently no reports on this aspect. Therefore, based on the folk application for fresh juice of C nutans, this study used metabonomics and network pharmacology to explore the material basis and mechanism of action of C nutans against RCC. Firstly, untargeted metabolomics profiling was performed by Liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry to screen the metabolites down-regulated by heat in the extract of C nutans. Secondly, we collected the targets of metabolites in the Swiss Target Prediction platform. In addition, the targets of RCC were obtained in the GeneCards database. The "component-target-disease" network was established by Cytoscape3.9.0 software. Then we constructed a protein-protein interaction network in the STRING network platform to screen core targets. The gene ontology and kyoto encyclopedia of genes and genomes enrichment analysis of core targets were carried out to predict the relevant pathway of C nutans in the treatment of RCC. Finally, the molecular docking verification of the core targets were carried out. In this study, 35 potential active ingredients and 125 potential targets were obtained. And the core targets were Cellular tumor antigen p53, Signal transducer and activator of transcription 3, and so on. Then, 48 biological processes, 30 cell components, and 36 molecular functions were obtained by gene ontology enrichment analysis. Besides, 44 pathways were obtained by Kyoto encyclopedia of genes and genomes enrichment analysis, including Pathway in cancer, PI3K-Akt signal pathway, P53 signal pathway, and so on. The docking model between the core target and its corresponding components was stable. This research is based on the folk application of C nutans, showed its potential active ingredients by metabonomics, and predicted the potential mechanism of C nutans in the treatment of RCC by network pharmacology. It provides new references for follow-up research and new drug development.

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