Triptolide targets

Background: Platinum-resistant ovarian cancer (PROC) is a major clinical challenge driven by profound intratumoral heterogeneity. Triptolide (TP) exhibits promising anti-tumor potential, yet its precise mechanisms within PROC remain elusive due to the limitations of traditional target-screening strategies. Methods: This study developed a comprehensive strategy integrating computational predictions with in vitro experimental validations. First, scRNA-seq data were processed to evaluate TP target genes predicted by SwissTargetPrediction, alongside pseudotime trajectory and CellChat intercellular communication analyses. Subsequently, an ensemble of six machine learning (ML) algorithms (LASSO, Random Forest, Boruta, Decision Tree, XGBoost, and GBM) was utilized to pinpoint the core therapeutic target. To verify direct molecular engagement, molecular docking, molecular dynamics (MD) simulations, and Surface Plasmon Resonance (SPR) assays were performed. Finally, the functional mechanism of the identified target in CDDP resistance was validated in vitro using parental SKOV3 and resistant SKOV3/CDDP cell lines. Results: scRNA-seq analysis revealed TP target genes are preferentially enriched in highly genomically unstable malignant epithelial cells. This subpopulation showed an aggressive intercellular communication profile, profound dependence on extracellular matrix (ECM) signals, and dominant secretion of the chemoresistance-related cytokine osteopontin (SPP1). Furthermore, the ML pipeline consistently pinpointed the proto-oncogene Conclusion: In conclusion, TP reverses CDDP resistance in PROC by downregulating