ArticleFrontiers in oncology2025
Network pharmacology combined with molecular docking and experimental validation of the mechanism of action of columbianetin acetate in the treatment of ovarian cancer.
Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Two Standards-Aided LC-MS Technologies Uncover 30 "Unreported" Compounds in Natural Bear Bile Powder to Add a New Pharmacopoeia Quality-Marker.Journal of separation science · 2026Article
- Catechin-Folate nano-niosomes from Osbeckia parvifolia Arn. induce apoptotic cell death in Ovarian cancer.Scientific reports · 2026Article
- Network pharmacology refined with non-ubiquity and decoy-controlled molecular docking reveals insights intoFrontiers in bioinformatics · 2026Article
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8 authors.
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Abstract
Background: Ovarian cancer is the most prevalent malignant tumor of the female reproductive system and has the highest mortality rate among gynecological cancers. Columbianetin acetate (CE) is one of the active ingredients of Angelica sinensis, which has good antifungal and anti-inflammatory activities. However, its potential mechanism of action in ovarian cancer remains unclear. This study used network pharmacology and molecular docking technology to investigate the molecular mechanism and material basis of CE in the treatment of ovarian cancer, and further verified by Methods: Relevant targets for CE were obtained from TCMSP and SwissTargetPrediction databases. OMIM, GeneCards and DisGeNET databases were applied to screen ovarian cancer-related targets. The STRING database to obtain protein-protein interaction (PPI) network. Then key targets were obtained using Cytoscape software, followed by expression, survival and ROC diagnostic analyses of core genes using R software. GO and KEGG enrichment analyses were performed using the DAVID database. Binding ability of CE to core targets was assessed by molecular docking. KEGG sites were used to predict core gene-related pathways. Subsequently, Results: A total of 55 CE-ovarian cancer interaction targets were identified using network pharmacology techniques. Among these, eight key targets -ESR1, GSK3B, JAK2, MAPK1, MDM2, PARP1, PIK3CA, and SRC-were screened using Cytoscape software. Core genes ESR1, GSK3B and JAK2 were obtained based on expression, prognostic and diagnostic values using R software. GO and KEGG enrichment analyses indicated that CE treatment of ovarian cancer might be related to PI3K/Akt signaling pathway, MAPK signaling pathway, ErbB signaling pathway and Ras signaling pathway. The molecular docking results showed that CE had good binding ability with core targets ESR1, GSK3B and JAK2. The results of Conclusions: Based on the network pharmacology approach, we predicted the potential mechanism of CE for the treatment of ovarian cancer, which provided a new idea for further research on its pharmacological mechanism.
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