Network pharmacology and molecular docking reveal the mechanism of Zishen Yutai Wan against polycystic ovary syndrome

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Authors: Zhu Ying, Zhu Hongqiu, Li Junjie, Wu Peijuan, Qian Zhang, Duan Mengxue, Li Yan
Cited by: 1
References: 33

Abstract

OBJECTIVES: The current treatments of polycystic ovarian syndrome (PCOS) have limited selectivity and effectiveness. Zishen Yutai Wan (ZSYTW) has shown therapeutic effects on patients with PCOS. This study aims to discover potential therapeutic targets and molecular mechanisms based on network pharmacology and molecular docking. METHODS: A disease gene set related to PCOS was collected from three public databases, a ZSYTW target gene set was established using the Traditional Chinese Medicine Systems Pharmacology database and Traditional Chinese Medicine and Chemical Components Database, and an intersection of two gene sets to obtain intersecting genes. Protein-protein interaction (PPI) network were performed on intersecting genes. Molecular docking further confirmed the high affinity and stability between the active compounds of ZSYTW and core targets. Finally, PCOS model mice were used to verify the results. RESULTS: Network pharmacology showed that AKT1, TNF, IL6, TP53, and ESR1 were the key targets of ZSYTW against PCOS. Molecular docking demonstrated beta-sitosterol and stigmasterol exhibit strong binding affinities and binding stability with core targets, and p53 has the highest affinity with core components of ZSYTW. Mice experiment showed that compared with the control group, the expression of p53 protein and total apoptosis rate of ovarian granulosa cells in PCOS group were significantly increased (P < 0.001). And ZSYTW could decrease the increased expression of P53 protein and total apoptosis rate of granulosa cells (P < 0.001). CONCLUSION: ZSYTW could effectively improve PCOS by regulating p53 and apoptosis of ovarian granulosa cells.

Fields of Study & Subjects

Ovarian function and disorders Reproductive System and Pregnancy Medicinal Plant Pharmacodynamics Research

Publication details

Journal / source
Journal of Ovarian Research
Publisher
Springer Science and Business Media LLC
Volume
19
Issue
1
Pages
52–52
Publication date
5 January 2026
Language
EN