Abstract
Aromatase inhibitors are the most important targets in treatment of estrogen-dependent cancers. In order to search for potent steroidal aromatase inhibitors (SAIs) with lower side effects and overcome cellular resistance, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of SAIs to build 3D QSAR models. The reliable and predictive CoMFA and CoMSIA models were obtained with statistical results (CoMFA: q2 = 0.636, r2ncv = 0.988, r2pred = 0.658; CoMSIA: q2 = 0.843, r2ncv = 0.989, r2pred = 0.601). This 3D QSAR approach provides significant insights that can be used to develop novel and potent SAIs. In addition, Genetic algorithm with linear assignment of hypermolecular alignment of database (GALAHAD) was used to derive 3D pharmacophore models. The selected pharmacophore model contains two acceptor atoms and four hydrophobic centers, which was used as a 3D query for virtual screening against NCI2000 database. Six hit compounds were obtained and their biological activities were further predicted by the CoMFA and CoMSIA models, which are expected to design potent and novel SAIs.
Highlights
Aromatase is a cytochrome P-450 dependent enzyme that catalyzes the aromatization of androgens to estrogens
In order to validate the obtained 3D Quantitative structure-activity relationship (QSAR) models, r2pred was used to determine the predictive abilities of the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models from the 16 compounds, which were not included in the generation of the models
In order to search for more potent steroidal aromatase inhibitors (SAIs) with lower side effects and overcome the drug resistance, 3D QSAR studies, pharmacophore modeling and virtual screening were performed
Summary
Aromatase is a cytochrome P-450 dependent enzyme that catalyzes the aromatization of androgens to estrogens. The non-steroidal aromatase inhibitors (NSAIs) are mostly azole type compounds, such as the clinically used anastrozole and letrozole, which compete with the substrate for binding to the enzyme active site [5]. The orally active exemestane is the main steroidal inhibitor [6] These SAIs mimic the natural substrate androstenedione and are converted by the enzyme to reactive intermediates, which bind irreversibly to the enzyme active site, resulting in inactivation of aromatase [7]. A pharmacophore model can be considered as the ensemble of steric and electrostatic features of different compounds, which are necessary to ensure optimal supramolecular interactions with a specific biological target structure and to trigger or to block its biological response. Test-set compounds; and b Compounds used to generate pharmacophore models
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