20, 3D and 40 QSAR studies relating flavanoid inhibitor activity in alpha estrogen receptors

With the discovery of the alpha-estrogen receptor, so-called selective estrogen receptor subtype modulators (SERSMs) may be even more selective, and therefore more efficient in hormone replacement causing less side effects associated to the development of breast and ovarian cancer. The present work aims at proposing 2D, 3D and 4D QSAR models based on 21 flavonoid compounds and derivatives relating the inhibitory activity in alpha estrogen receptors. Field descriptors were calculated with LQTAGrid program, while the 4D-QSAR descriptors with LQTA-QSAR methodology (includes the conformational variation in the model). The data set was split into a training (16 compounds) and test (5 compounds) sets. As a result of this work, a 2D model was obtained containing an electronic descriptor and other topological descriptors from the Dragon program. The models were obtained and validated using QSAR Modeling. The PLS models and statistical parameters obtained are shown below: 2D model: 10 molecular descriptors (MDs), 41atent variables (LVs), R2= 0.970, Q2LOO= 0.710; R2pred= 0.686 3D model: 4 MDs, 4 LVs, R2= 0.917, Q2LOO= 0.807, R2pred= 0.703 4D model: 6 MDs, 1 LV, R2= 0.860. Q2LOO= 0.797, R2pred= 0.506 The models were validated regarding their robustness and chance correlation using leave-N-out and yrandomization tests, respectively, and all models passed in these tests. The descriptors selected in the three models will be analyzed for a future interpretation of the mechanism of action of these compounds in alpha estrogen receptors.