RÉSUMÉ
Synthetic selective modulators of the estrogen receptors (SERMs) have shown to protect neurons and glial cells against toxic insults. Among the most relevant beneficial effects attributed to these compounds are the regulation of inflammation, attenuation of astrogliosis and microglial activation, prevention of excitotoxicity and as a consequence the reduction of neuronal cell death. Under pathological conditions, the mechanism of action of the SERMs involves the activation of estrogen receptors (ERs) and G protein-coupled receptor for estrogens (GRP30). These receptors trigger neuroprotective responses such as increasing the expression of antioxidants and the activation of kinase-mediated survival signaling pathways. Despite the advances in the knowledge of the pathways activated by the SERMs, their mechanism of action is still not entirely clear, and there are several controversies. In this review, we focused on the molecular pathways activated by SERMs in brain cells, mainly astrocytes, as a response to treatment with raloxifene and tamoxifen.
Sujet(s)
Astrocytes/effets des médicaments et des substances chimiques , Encéphalopathies/traitement médicamenteux , Neuroprotecteurs/pharmacologie , Chlorhydrate de raloxifène/pharmacologie , Récepteurs des oestrogènes/métabolisme , Modulateurs sélectifs des récepteurs des oestrogènes/métabolisme , Modulateurs sélectifs des récepteurs des oestrogènes/pharmacologie , Tamoxifène/pharmacologie , Animaux , HumainsRÉSUMÉ
The estrogen receptor, ER, is an important biological target whose inhibition is known to be therapeutically relevant in the treatment of postmenopausal osteoporosis. In the present study, two prediction methods (CoMFA and GRIND (Almond)) were used to describe the binding modes of a set of estrogen receptor ligands. The critical alignment step presented in CoMFA was solved by using the information of the molecular descriptors space generated by grid-independent descriptors (GRIND). Then, it was possible to build robust and high predictive models based on the alignment-independent model. Since the structure of estrogen receptor is solved, the results of the present 3D QSAR models, given by the PLS maps based on molecular interaction fields (MIF) were compared to ligand-binding ER domains and showed good agreement.