Exploring the mechanism of Stephania tetrandra S. Moore in the treatment of cisplatin resistance against ovarian cancer through integration of network pharmacology and molecular docking

Zhong, Yuanyuan and Cai, Shanshan and Fang, Chunyue and Dai, Wei (2025) Exploring the mechanism of Stephania tetrandra S. Moore in the treatment of cisplatin resistance against ovarian cancer through integration of network pharmacology and molecular docking. Medicine, 104 (46): e45860. ISSN 0304-5412

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Abstract

Cisplatin resistance is a major contributor to treatment failure in ovarian cancer (OC). This study investigates the mechanisms of action and therapeutic targets of Stephania tetrandra S. Moorefor cisplatin-resistant OC. OC datasets were obtained from the gene expression omnibus database, and differentially expressed genes were identified through weighted gene co-expression network analysis. Cisplatin resistance-related targets were screened using the GeneCards, OMIM, and MsigDB databases, while active components of S tetrandra were retrieved from the TCMSP, ETCM, and BATMAN databases. Commonly shared genes between these 2 sets were selected for further analysis. A protein-protein interaction network was constructed using the STRING database, and 4 machine learning algorithms were integrated to identify core targets. Binding affinities were evaluated by molecular docking with AutoDock Vina. Molecular dynamics simulations were then conducted to assess the stability of the ligand-target complexes. We performed ADMET analysis to assess the pharmacokinetic properties and drug-likeness of S tetrandra. Machine learning algorithms further identified 8 core targets including threonine tyrosine kinase (TTK), AURKA, B-cell lymphoma 2, vitamin D receptor, NFKB1, cyclin dependent kinase 1, DNMT1, and SMAD7. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed that these targets were significantly enriched in pathways such as the PI3K-AKT, cell cycle regulation, p53 signaling pathway, and platinum resistance pathway. Receiver operating characteristic curve analysis demonstrated diagnostic potential for all genes except SMAD7 (AUC = 0.603 < 0.7). Immune infiltration analysis indicated a positive correlation between AURKA/TTK expression and M0/M1 macrophage infiltration (P