Literature DB >> 27485195

Pharmacophore Model Refinement for 11β-Hydroxysteroid Dehydrogenase Inhibitors: Search for Modulators of Intracellular Glucocorticoid Concentrations.

Anna Vuorinen1, Lyubomir G Nashev2, Alex Odermatt2, Judith M Rollinger3, Daniela Schuster4.   

Abstract

11β-Hydroxysteroid dehydrogenases (11β-HSD) control the intracellular concentrations of glucocorticoids: 11β-HSD1 converts the inactive cortisone to the active cortisol, and 11β-HSD2 is responsible for the opposite reaction. Inhibition of 11β-HSD1 is beneficial in the treatment of metabolic syndrome, whereas 11β-HSD2 inhibition leads to hypertension. Therefore, 11β-HSD1 inhibitors should be selective over 11β-HSD2. To support drug discovery and toxicological studies, we have previously reported pharmacophore models for 11β-HSD1 and 2 inhibition. These models represent the common chemical features of 11β-HSD inhibitors, which were used as virtual screening filter. Since new inhibitors are constantly discovered, the quality of the pharmacophore models has to be evaluated in order to maintain a good predictive power. In this study, we report a systematic evaluation and refinement of our pharmacophore model collection. We employed our models for virtual screening, especially focusing on the 11β-HSD2 inhibition. In total, 42 compounds were biologically evaluated and among these we discovered 17 11β-HSD inhibitors that decreased the residual enzyme activity to 50% or less at the concentration of 20 µM. The experimental 11β-HSD1 and 2 readouts from these compounds were used for further model refinement. Evaluation metrics were applied for a quantitative comparison of the old and newly generated models which resulted in a set of improved pharmacophore models offering reliable in silico tools for the identification of novel and selective 11β-HSD inhibitors.
Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  11β-Hydroxysteroid dehydrogenase; Enzyme inhibitor; Model refinement; Pharmacophore model; Virtual screening

Year:  2013        PMID: 27485195     DOI: 10.1002/minf.201300063

Source DB:  PubMed          Journal:  Mol Inform        ISSN: 1868-1743            Impact factor:   3.353


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