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@article{179254,
        author = {Pallavi kavitake and Ritesh jagtap and Rutuja jagdale and Snehal koli and Amit panskar},
        title = {Network pharmacology of 10-gingerol},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {6394-6402},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179254},
        abstract = {The present study explores the therapeutic potential of 10-gingerol, a key bioactive compound derived from Zingiber officinale, using an integrated network pharmacology and molecular modeling approach. 10-Gingerol is known for its diverse pharmacological properties, including anti-inflammatory, antioxidant, anticancer, and antimicrobial activities. To elucidate its multi-target mechanisms, potential gene and receptor interactions were identified using Swiss Target Prediction and cross-validated with databases such as SEA, MalaCards, OMIM, and DisGeNET. Common gene targets were refined using AI-assisted tools and Venny 2.1.0, while pathway enrichment analysis was performed using the Reactome Pathway Database. Cytoscape and STRING were employed to construct and analyze protein-protein interaction networks, emphasizing central nodes based on topological features. Molecular modeling techniques provided insights into binding affinities and structural interactions at the atomic level. The study reveals that 10-gingerol modulates key signaling pathways, particularly those involved in inflammation, cancer, and metabolic disorders. These findings demonstrate the power of combining computational approaches to deepen mechanistic understanding and advance the development of natural product-based therapeutics.},
        keywords = {Network Pharmacology, Gene,10-Gingerol},
        month = {May},
        }