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@article{178340,
        author = {Snehal Koli and Shweta Jamdade and Gaytri Botre and Pallavi Kavitake and Ritesh Jagtap and Rutuja Jagdale and Dr. A.N. Panaskar},
        title = {Network Pharmacology of rostafuroxin},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {4666-4675},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178340},
        abstract = {The present study employs an integrated network pharmacology approach to investigate the gene and receptor associations of lead compounds, with a particular focus on the antihypertensive agent rostafuroxin. Molecular structures were retrieved from the PubChem database in SMILES format and analyzed using Swiss Target Prediction to obtain corresponding UniProt IDs. Further gene identification was conducted using the Similarity Ensemble Approach (SEA) and cross-referenced with bioinformatics resources including Mala Cards, OMIM, and Disgenet. Overlapping gene targets were identified using artificial intelligence tools and visualized with Venny 2.1.0. Pathway enrichment analysis was performed using Reactome, while protein–protein interaction networks were constructed and analyzed via Cytoscape’s STRING plugin to determine key network nodes based on centrality metrics. This comprehensive workflow highlights the utility of network pharmacology in elucidating multi-target drug mechanisms. By integrating computational tools with systems biology, the study provides novel insights into the pharmacological actions of rostafuroxin and supports the broader application of network-based drug discovery strategies in treating complex diseases such as hypertension.},
        keywords = {Network pharmacology, Rostafuroxin, SwissTargetPrediction, Hypertension, Cytoscape, STRING, Bioinformatics, Drug discovery, Multi-target therapy, Systems biology},
        month = {May},
        }