3D QSAR Studies, Pharmacophore Modeling and Virtual Screening on a Series of Steroidal Aromatase Inhibitors
نویسندگان
چکیده
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, r²(ncv) = 0.988, r²(pred) = 0.658; CoMSIA: q² = 0.843, r²(ncv) = 0.989, r²(pred) = 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.
منابع مشابه
Correction: Xie, H.; et al. 3D QSAR Studies, Pharmacophore Modeling and Virtual Screening on a Series of Steroidal Aromatase Inhibitors. Int. J. Mol. Sci. 2014, 15, 20927–20947
A number of sentences in the first paragraph of the introduction of [28] were copied verbatim from [21,22,25,29]. Although [21,22,25] were cited in the text, [29] was omitted and it was not made sufficiently clear that direct quotations were used. The authors wish to apologize to the authors of [21,22,25,29] and to the readers of the journal for any inconvenience.
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