Network pharmacology-based strategy to investigate anticancer mechanisms of Catharanthus roseus (L.) G. Don

doi:10.5246/jcps.2023.11.073

Abstract

Abstract:

In the present study, the bioinformatics analysis tool BATMAN-TCM was employed to explore the molecular mechanism of action of Catharanthus roseus (C. roseus) in cancer treatment. The potential targets of C. roseus were predicted using BATMAN-TCM, and the GeneCards database was utilized to identify cancer-related targets. A compound-disease-target interaction network was constructed using Cytoscape 3.7.0 software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to determine the gene functions of C. roseus in counteracting cancer. Nine types of active ingredients were identified from C. roseus, and a compound-disease-target network was established. The protein-protein interaction (PPI) network of C. roseus targets was constructed using the STRING database, comprising 55 nodes and 328 interaction relationships. Key nodes in the network included CTNNB1, JUN, VEGFA, ESR1, HIF1A, FOS, and MTOR. GO analysis identified 73 items, such as RNA polymerase II-specific DNA-binding transcription factor binding, DNA-binding transcription factor binding, ubiquitin protein ligase binding, and ubiquitin-like protein ligase binding. In the KEGG pathway enrichment analysis, 106 signaling pathways were identified, with the PI3K-Akt signaling pathway and HIF-1 signaling pathway emerging as key pathways related to cancer. Overall, the research demonstrated that C. roseus exerted its anticancer effects through the synergistic regulation of multiple components, targets, and pathways. These findings provided a theoretical and scientific basis for the application of C. roseus in cancer treatment.

Key words: C. roseus, Network pharmacology, Active compounds, Cancer

Supporting:

Yuqian Zhang, Haiying Niu, Yiran Jin. Network pharmacology-based strategy to investigate anticancer mechanisms of Catharanthus roseus (L.) G. Don[J]. Journal of Chinese Pharmaceutical Sciences, 2023, 32(11): 911-922.

Figures/Tables 7

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