Integration of Bioinformatics and Pharmacological Network for Exploring the Potential of Curcumin as a Herbal Medicine for Adenomyosis
This study used bioinformatics and pharmacological networks to identify EPHA5, EPHB2, and EPHA4 as key targets for curcumin's potential therapeutic effects in adenomyosis, with axon guidance implicated as a key pathway.
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The paper uses an integrated bioinformatics and pharmacological network approach to investigate curcumin, a plant-derived compound, as a potential therapeutic agent for adenomyosis. Using pharmacological network data, protein–protein interaction networks (STRING) and hub-gene identification (CytoHubba) highlighted EPHA5, EPHB2, and EPHA4 as top nodes, while compound–target–disease interaction analysis and GO/KEGG enrichment implicated the axon guidance pathway as significantly enriched. Molecular docking was used to assess stable binding affinities between curcumin and target proteins, providing theoretical and experimental evidence. The main caveat is that the work is based on in silico network/database integration and docking rather than clinical validation, so mechanistic implications require further exploration. This paper is centrally about endometriosis and/or adenomyosis — it is specifically focused on adenomyosis and proposes curcumin’s targets and pathways for this condition.
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