Background: CKD is a progressive, irreversible condition characterised by the gradual decline in kidney function. CKD patients are frequently subjected to polypharmacotherapy for complications and comorbidities, resulting in a significantly high ADRs. It is necessary to achieve the optimal pharmacotherapy taking into account the patterns of drug utilization. Aim: To describe the use of drugs in CKD and study mechanisms of action of frequently prescribed agents at different stages of CKD using an in silico comparative analysis. Methods: Three frequently used drugs (Torsemide, Febuxostat and Furosemide) were studied. The structures of drugs were downloaded in SDF format from PubChem. ADMETlab 3.0 and Lipinski’s Rule of Five were used to evaluate the pharmacokinetic properties and drug-likeness. The target proteins were predicted with Swiss Target Prediction, and the CKD-related genes were all obtained from GeneCards. Intersecting targets were then processed by the STRING and visualized in Cytoscape to identify hub genes. AutoDock Vina was employed for molecular docking and ShinyGO was used for function enrichment analysis. Structures were obtained from RCSB PDB, and pictures of drug-target interactions produced with PyMOL. Results: Network pharmacology analysis identified 205 shared targets and 10 key hub genes (SRC, HSP90AA1, BCL2, PPARG, PTGS2, GSK3B, BCL2L1, MAPK14, RHOA, and MTOR) linked to inflammation, oxidative stress, apoptosis, and metabolic regulation. Major enriched pathways included PI3K-Akt, cAMP, lipid and atherosclerosis, and nitrogen metabolism. Docking studies demonstrated strong binding affinities (−4.3 to −8.8 kcal/mol), with Torsemide showing the highest stability, followed by Febuxostat & Furosemide. Conclusion: The study highlights the importance of multi-target pharmacotherapy in CKD management, with Torsemide demonstrating superior therapeutic potential.
Mounika* et al. (Fri,) studied this question.