Abstract
The G protein-coupled bile acid receptor (GPBAR1) has been recognized as a promising new target for the treatment of diverse diseases, including obesity, type 2 diabetes, fatty liver disease and atherosclerosis. The identification of novel and potent GPBAR1 agonists is highly relevant, as these diseases are on the rise and pharmacological unmet therapeutic needs are pervasive. Therefore, the aim of this study was to develop a proficient workflow for the in silico prediction of GPBAR1 activating compounds, primarily from natural sources. A protocol was set up, starting with a comprehensive collection of structural information of known ligands. This information was used to generate ligand-based pharmacophore models in LigandScout 4.08 Advanced. After theoretical validation, the two most promising models, namely BAMS22 and TTM8, were employed as queries for the virtual screening of natural product and synthetic small molecule databases. Virtual hits were progressed to shape matching experiments and physicochemical clustering. Out of 33 diverse virtual hits subjected to experimental testing using a reporter gene-based assay, two natural products, farnesiferol B (27) and microlobidene (28), were confirmed as GPBAR1 activators reaching more than 50% receptor activation at 20 μM with EC50s of 13.53 μM and 13.88 μM, respectively. This activity is comparable to that of the endogenous ligand lithocholic acid (1). Seven further virtual hits showed activity reaching at least 15% receptor activation either at 5 or 20 μM, including new scaffolds from natural and synthetic origin.