Identification of PPAR β/δ agonists using a drug-repurposing approach by computational HTVS and molecular docking/ dynamics simulation

Abstract

Abstract Peroxisome proliferator-activated receptors (PPARs) play a crucial role in regulating carbohydrate and lipid metabolism and are considered as significant targets for treating metabolic syndrome and cancers. There is a need to identify new bioactive ligands that can activate specific PPAR subtypes, particularly PPARβ/δ, which is less studied compared to other PPAR isoforms (α and γ). Here, the ZINC database of clinically approved drugs was screened to target PPARβ/δ receptor, through virtual screening followed by molecular docking and molecular dynamics (MD) simulation. Among the screened ligands, the top five ligands with strong binding affinity towards the PPARβ/δ were canagliflozin, empagliflozin, lumacaftor, eprosartan, dapagliflozin. The top-scoring ligands showed stable protein-ligand complexation (PLC)with PPARβ/δ, as revealed by RMSD / RMSF analysis. The in silico ADMET prediction analysis assessed the pharmacokinetic profiles of these top five ligands, wherein they showed favourable drug-likeness properties. These promising results indicate scope for developing and validating the top-scoring PPARβ/δ agonists in specific disease models.