Shalaparni’s dual therapeutic potential in rheumatoid arthritis and depression: a bioinformatics study

Abstract

Rheumatoid arthritis (RA) is a chronic inflammatory disease that is frequently accompanied by depression, suggesting shared inflammatory pathways. This study investigated Desmodium gangeticum (Shalaparni), an Ayurvedic herb containing the anti-inflammatory compound Gangetin, as a potential dual-acting therapeutic agent for RA and depression. We employed an integrative bioinformatics approach to explore the potential of Gangetin, a phytoconstituent of Shalaparni, as a dual-acting therapy. Target genes for RA and depression were retrieved from the DisGeNet database, while predicted molecular targets of Shalaparni were identified using SwissTargetPrediction. BioVenn was then used to visualize and identify overlapping genes among the RA-associated, depression-associated, and Shalaparni-target gene sets. A protein–protein interaction network was constructed using STRING and analyzed using Cytoscape. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted using the DAVID tool. Molecular docking of Gangetin, a phytochemical in Shalaparni, was performed with the top identified proteins using CB Dock. We identified 34 differentially expressed genes shared among RA, depression, and Shalaparni. The PPI network revealed significant interactions with hub genes, such as EGFR, BCL2, GSK3β, PIK3CA, and AKT1. Docking studies showed that Gangetin had high binding affinities with AKT1 and PIK3CA, indicating its potential to target key inflammatory pathways involved in both RA and depression. Shalaparni, through its active compound Gangetin, demonstrated potential as a dual-acting therapeutic agent for RA and depression by targeting shared inflammatory pathways. Further experimental validation is required to explore its clinical application.