Computational biology and chemistry · 2026
Synergistic action of Yinyanghuo A and Magnograndiolide against ovarian cancer: A computational prediction of targets and mechanism via network pharmacology and molecular simulations.
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Wang Jun, Liu Jinlong, Chen Qingjuan, Zhou Juan, Huo Anni, Zhang Wei, Cao Xia, Chen Wang
Аннотация
BACKGROUND: Ovarian cancer is a prevalent gynecologic malignancy. Despite multimodal treatment centered on surgery and supplemented by chemo and targeted therapy, challenges such as drug resistance and surgical trauma persist, underscoring the need for new approaches. Epimedium, a traditional Chinese medicine, has shown preliminary anti-ovarian cancer activity, warranting systematic investigation. This study applied network pharmacology and computational simulations to elucidate its molecular mechanisms and virtually screen for potential therapeutic compounds.
METHODS: To identify potential therapeutic targets, ovarian cancer-associated genes were retrieved from the GeneCards, OMIM, and TTD databases. Concurrently, active components of Epimedium were filtered from TCMSP employing pharmacokinetic thresholds. The resulting intersection of targets was analyzed through functional enrichment and PPI network analysis. The interactions between the key components and core targets were further validated by molecular docking and molecular dynamics simulations.
RESULTS: Network pharmacology identified that Epimedium treats ovarian cancer by modulating immunity, cellular stress, death, and proliferation via key targets such as EGFR, SRC, and PI3K subunits (PIK3CA, PIK3CB, PIK3R1). The compounds Yinyanghuo A and Magnograndiolide, which show strong binding to these targets, are predicted to function through EGFR inhibition, leading to suppression of the PI3K-AKT axis and consequent inhibition of tumor proliferation and metastasis.
CONCLUSION: This study systematically elucidates the multi-component, multi-target, and multi-pathway mechanisms underlying Epimedium's anti-ovarian cancer effects, thereby providing a theoretical foundation for its potential clinical application. It should be noted, however, that these findings are computational predictions and thus require experimental validation.
METHODS: To identify potential therapeutic targets, ovarian cancer-associated genes were retrieved from the GeneCards, OMIM, and TTD databases. Concurrently, active components of Epimedium were filtered from TCMSP employing pharmacokinetic thresholds. The resulting intersection of targets was analyzed through functional enrichment and PPI network analysis. The interactions between the key components and core targets were further validated by molecular docking and molecular dynamics simulations.
RESULTS: Network pharmacology identified that Epimedium treats ovarian cancer by modulating immunity, cellular stress, death, and proliferation via key targets such as EGFR, SRC, and PI3K subunits (PIK3CA, PIK3CB, PIK3R1). The compounds Yinyanghuo A and Magnograndiolide, which show strong binding to these targets, are predicted to function through EGFR inhibition, leading to suppression of the PI3K-AKT axis and consequent inhibition of tumor proliferation and metastasis.
CONCLUSION: This study systematically elucidates the multi-component, multi-target, and multi-pathway mechanisms underlying Epimedium's anti-ovarian cancer effects, thereby providing a theoretical foundation for its potential clinical application. It should be noted, however, that these findings are computational predictions and thus require experimental validation.