Lead optimization providing a series of flavone derivatives as potent nonsteroidal inhibitors of the cytochrome P450 aromatase enzyme.

Following our SAR studies on aromatase inhibitors, new compounds were designed by appropriately modifying the structure of flavone 1 using our previously reported CoMFA model. While the introduction of substituents on the 2-phenyl ring alone did not cause improvement in potency, these modifications and the removal of the 7-methoxy group led to compounds showing inhibitory activity in the nanomolar range, comparable to the marketed drug fadrozole.

Enantioselective nonsteroidal aromatase inhibitors identified through a multidisciplinary medicinal chemistry approach.

To identify enantioselective nonsteroidal aromatase inhibitors, a multidisciplinary medicinal chemistry approach was pursued. First, our earlier CoMFA model [Bioorg. Med. Chem. 1998,6, 377-388] was extended taking purposely into account previously discovered enantioselective aromatase inhibitors. The 3D QSAR model was then exploited to design chiral ligands, whose configurational assignment was obtained, after HPLC separation, by means of a combination of circular dichroism measurements and time dependent density functional calculations. Finally, the new enantiomeric inhibitors were separately tested to ascertain both their potency against the cytochrome P450 aromatase (CYP19; EC 1.14.14.1), and their selectivity relative to another enzyme of the P450 family. A satisfactory agreement between experimental and predicted data allowed us to assert that a properly built "enantioselective CoMFA model" might constitute a useful tool for addressing enantioselective ligands design.

Design, synthesis, and 3D QSAR of novel potent and selective aromatase inhibitors.

The design, synthesis, and biological evaluation of a series of new aromatase inhibitors bearing an imidazole or triazole ring linked to a fluorene (A), indenodiazine (B), or coumarin scaffold (C) are reported. Properly substituted coumarin derivatives displayed the highest aromatase inhibitory potency and selectivity over 17-alpha-hydroxylase/17-20 lyase. The modeling of the aromatase inhibition data by Comparative Molecular Field Analysis (CoMFA/GOLPE 3D QSAR approach) led to the development of a PLS model with good fitting and predictive powers (n = 22, ONC = 3, r(2) = 0.949, s = 0.216, and q(2) = 0.715). The relationship between aromatase inhibition and the steric and electrostatic fields generated by the examined azole inhibitors enables a clear understanding of the nature and spatial location of the main interactions modulating the aromatase inhibitory potency.