ArticleFrontiers in medicine2025
A reverse network pharmacology and bioinformatics-based approach to exploring medication patterns for polycystic ovary syndrome-related infertility.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: To predict potential herbal medicines targeting polycystic ovary syndrome (PCOS)-related infertility using an in silico reverse network pharmacology approach and identify core herbal candidates. Methods: This computational study began by collecting disease targets for PCOS and infertility from multiple public databases. Common targets were identified, and active compounds associated with these targets were retrieved from the Uniprot and TCMSP databases. These compounds were subsequently filtered using PubChem and SwissADME based on pharmacokinetic properties and mapped to corresponding herbs via TCMSP. Herbal properties (nature, flavor, meridian tropism) were statistically analyzed. A core network of targets-compounds-herbs was constructed using Cytoscape 3.8.0, and a subnetwork was generated from nodes with a Degree > 20. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on the targets of the core herbal combination to elucidate potential mechanisms. Results: A total of 2,500 common targets for PCOS and infertility, 1,545 active compounds, and 488 corresponding herbs were identified. Analysis of herbal properties revealed a predominance of Warm and Pungent medicines, followed by Cold, Bitter, Neutral, and Sweet medicines. A core herbal combination consisting of Conclusion: This study successfully employed reverse network pharmacology to predict a core herbal combination for treating PCOS-related infertility. The findings, while requiring experimental validation, offer novel insights for developing therapeutic strategies and provide a foundation for future clinical management.
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