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Updated: Jan 10, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
Decoding gout pathogenesis: target discovery and drug design through computational models
Hemantha Mani Kumar Chakravarthi Chanda1, Sudheer Kumar Katari1, Tejaswini Tiyyagura1
1Department of Biotechnology, Vignan's Foundation for Science, Technology and Research(Deemed to be University), Vadlamudi, Guntur, 522213 India.
Abstract:
The study presents a comprehensive approach to target prediction for gout (DOID: 13189) through the integration of disease ontology and network-based strategies. A total of 13 proteins associated with gout were identified and analyzed using the STRING database, which visualized protein-protein interactions (PPIs). Cytoscape, enhanced with the CytoHubba plugin, was used to prioritize key proteins, identifying Solute loading carrier family 22 member 12 (SLC22A12) and SLC22A9 genes as the most promising targets based on their high degree of interaction. Sequence alignment of these proteins (Urate Anion Exchanger 1-URAT1 and Organic anion transporter 7-OAT7) revealed significant homology, suggesting that they play complementary roles in uric acid transport and gout pathogenesis. Molecular docking by AutoDock Vina and AutoDock4 of whole Indian Medicinal Plants, Phytochemistry And Therapeutics (IMPPAT) database, Food and Drug Administration (FDA) Approved Drugs revealed three leads from the Woodfordia fruticosa (Heterophylliin A), Arctium lappa (Arctignan D), and Oroxylum indicum (Scutellarein 7-rutinoside) demonstrated strong binding affinities with URAT1 through favorable docking interactions over the best docked Fostemsavir and URAT1 inhibitors (Lesinurad and Benzbromarone) indicating their potential as modulators of uric acid transport. The molecular dynamics simulations (MDS) of URAT1 in membrane environment with the identified compounds by Desmond further supported that all three leads exhibited superior binding stability, binding energy and interaction profiles compared to the existing drugs. The results highlight the potential of these phytochemicals upon further experimental validation as therapeutic agents for gout. This integrative bioinformatics and computational approach provide a robust framework for discovering potent drug target and bioactive compounds with strong potential for effective gout treatment if further validated through in vitro and in vivo assays.
Supplementary Information:
The online version contains supplementary material available at 10.1007/s40203-025-00476-5.
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