Suppr超能文献

Binding properties of [3H]gacyclidine (cis(pip/me)-1-[1-(2-thienyl)-2-methylcyclohexyl]piperidine) enantiomers in the rat central nervous system.

作者信息

Hirbec H, Teilhac J, Kamenka J, Privat A, Vignon J

机构信息

INSERM U336, DPVSN, ENSC Montpellier, 8 rue de l'école normale, 34296, Montpellier, France.

出版信息

Brain Res. 2000 Mar 24;859(2):177-92. doi: 10.1016/s0006-8993(99)02420-8.

Abstract

Gacyclidine (cis(pip/me)-1-[1-(2-thienyl)-2-methylcyclohexyl]piperidine) is a TCP derivative, which exhibits potent neuroprotective properties against glutamate-induced neurotoxicity in vitro and in vivo. In order to better understand gacyclidine pharmacological properties, the binding parameters of its enantiomers ((-) and (+)[3H]GK11) were determined in the rat central nervous system (CNS). An autoradiographic study has shown that their binding distributions are correlated with those of N-methyl-D-aspartate (NMDA) receptors throughout the CNS. Globally, the labeling was the highest with (-)[3H]GK11. In the cerebellum, both radioligands similarly labeled the molecular layer. For both radioligands, on telencephalic, cerebellum and spinal cord homogenates, the association and dissociation kinetics were accounted for by multiphasic process. In all regions, (-)[3H]GK11 exhibited the highest affinity in the nanomolar range. The pharmacological study revealed that both enantiomers labeled both high and low affinity sites in all regions. The pharmacological profile of high affinity sites was correlated with those of NMDA receptors. Those of low affinity sites were different in telencephalic and cerebellar homogenates. Overall, this study showed that low affinity sites might constitute a heterogeneous population, which could include sigma receptors in the cerebellum. The autoradiographic study has shown that these sites may be located in the molecular layer. The contribution of low affinity sites to the neuroprotective properties of gacyclidine remains to be investigated.

摘要

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验