Abstract
17β-Hydroxysteroid dehydrogenase type 1 (17β-HSD1) catalyzes the last step of the estrogen biosynthesis, namely the reduction of estrone to the biologically potent estradiol. As such it is a potentially attractive drug target for the treatment of estrogen-dependent diseases like breast cancer and endometriosis. 17β-HSD1 belongs to the bisubstrate enzymes and exists as an ensemble of conformations. These principally differ in the region of the βFαG′-loop, suggesting a prominent role in substrate and inhibitor binding. Although several classes of potent non-steroidal 17β-HSD1 inhibitors currently exist, their binding mode is still unclear. We aimed to elucidate the binding mode of bis(hydroxyphenyl)arenes, a highly potent class of 17β-HSD1 inhibitors, and to rank these compounds correctly with respect to their inhibitory potency, two essential aspects in drug design. Ensemble docking experiments resulted in a steroidal binding mode for the closed enzyme conformations and in an alternative mode for the opened and occluded conformers with the inhibitors placed below the NADPH interacting with it synergically via π–π stacking and H-bond formation. Both binding modes were investigated by MD simulations and MM-PBSA binding free energy estimations using as representative member for this class compound 1 (50 nM). Notably, only the alternative binding mode proved stable and was energetically more favorable, while when simulated in the steroidal binding mode compound 1 was displaced from the active site. In parallel, ab initio studies of small NADPH-inhibitor complexes were performed, which supported the importance of the synergistic interaction between inhibitors and cofactor.
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MN is grateful for his co-tutelle PhD between the University of Bologna and Saarland University of which this work was a substantial part.
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Negri, M., Recanatini, M. & Hartmann, R.W. Computational investigation of the binding mode of bis(hydroxylphenyl)arenes in 17β-HSD1: molecular dynamics simulations, MM-PBSA free energy calculations, and molecular electrostatic potential maps. J Comput Aided Mol Des 25, 795–811 (2011). https://doi.org/10.1007/s10822-011-9464-7
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DOI: https://doi.org/10.1007/s10822-011-9464-7