Title |
Targeting Bile Acid Receptors: Discovery of a Potent and Selective Farnesoid X Receptor Agonist as a New Lead in the Pharmacological Approach to Liver Diseases
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Published in |
Frontiers in Pharmacology, March 2017
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DOI | 10.3389/fphar.2017.00162 |
Pubmed ID | |
Authors |
Carmen Festa, Simona De Marino, Adriana Carino, Valentina Sepe, Silvia Marchianò, Sabrina Cipriani, Francesco S. Di Leva, Vittorio Limongelli, Maria C. Monti, Angela Capolupo, Eleonora Distrutti, Stefano Fiorucci, Angela Zampella |
Abstract |
Bile acid (BA) receptors represent well-defined targets for the development of novel therapeutic approaches to metabolic and inflammatory diseases. In the present study, we report the generation of novel C-3 modified 6-ethylcholane derivatives. The pharmacological characterization and molecular docking studies for the structure-activity rationalization, allowed the identification of 3β-azido-6α-ethyl-7α-hydroxy-5β-cholan-24-oic acid (compound 2), a potent and selective FXR agonist with a nanomolar potency in transactivation assay and high efficacy in the recruitment of SRC-1 co-activator peptide in Alfa Screen assay. In vitro, compound 2 was completely inactive towards common off-targets such as the nuclear receptors PPARα, PPARγ, LXRα, and LXRβ and the membrane G-coupled BA receptor, GPBAR1. This compound when administered in vivo exerts a robust FXR agonistic activity increasing the liver expression of FXR-target genes including SHP, BSEP, OSTα, and FGF21, while represses the expression of CYP7A1 gene that is negatively regulated by FXR. Collectively these effects result in a significant reshaping of BA pool in mouse. In summary, compound 2 represents a promising candidate for drug development in liver and metabolic disorders. |
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Mendeley readers
Geographical breakdown
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Unknown | 35 | 100% |
Demographic breakdown
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Researcher | 11 | 31% |
Student > Ph. D. Student | 6 | 17% |
Student > Bachelor | 3 | 9% |
Professor > Associate Professor | 2 | 6% |
Student > Master | 1 | 3% |
Other | 3 | 9% |
Unknown | 9 | 26% |
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Computer Science | 3 | 9% |
Other | 2 | 6% |
Unknown | 7 | 20% |