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血脑屏障胆碱转运体潜在阳离子载体介导转运的预测筛选模型。

Predictive screening model for potential vector-mediated transport of cationic substrates at the blood-brain barrier choline transporter.

机构信息

Department of Pharmaceutical Sciences, Texas Tech University Health Sciences Center, School of Pharmacy, Amarillo, TX 79106-1712, USA.

出版信息

Bioorg Med Chem Lett. 2010 Feb 1;20(3):870-7. doi: 10.1016/j.bmcl.2009.12.079. Epub 2009 Dec 28.

Abstract

A set of semi-rigid cyclic and acyclic bis-quaternary ammonium analogs, which were part of a drug discovery program aimed at identifying antagonists at neuronal nicotinic acetylcholine receptors, were investigated to determine structural requirements for affinity at the blood-brain barrier choline transporter (BBB CHT). This transporter may have utility as a drug delivery vector for cationic molecules to access the central nervous system. In the current study, a virtual screening model was developed to aid in rational drug design/ADME of cationic nicotinic antagonists as BBB CHT ligands. Four 3D-QSAR comparative molecular field analysis (CoMFA) models were built which could predict the BBB CHT affinity for a test set with an r(2) <0.5 and cross-validated q(2) of 0.60, suggesting good predictive capability for these models. These models will allow the rapid in silico screening of binding affinity at the BBB CHT of both known nicotinic receptor antagonists and virtual compound libraries with the goal of informing the design of brain bioavailable quaternary ammonium analogs that are high affinity selective nicotinic receptor antagonists.

摘要

一组半刚性环状和非环状双季铵盐类似物,是旨在鉴定神经元烟碱型乙酰胆碱受体拮抗剂的药物发现计划的一部分,进行了研究,以确定在血脑屏障胆碱转运体(BBB CHT)上的亲和力的结构要求。这种转运体可能作为阳离子分子进入中枢神经系统的药物输送载体具有实用性。在当前的研究中,开发了一个虚拟筛选模型,以辅助阳离子烟碱拮抗剂作为 BBB CHT 配体的合理药物设计/ADME。建立了四个 3D-QSAR 比较分子场分析(CoMFA)模型,可预测测试集的 BBB CHT 亲和力,r(2) <0.5,交叉验证 q(2)为 0.60,表明这些模型具有良好的预测能力。这些模型将允许快速在计算机上筛选已知烟碱受体拮抗剂和虚拟化合物文库与设计脑可生物利用的季铵盐类似物的结合亲和力,这些类似物是高亲和力选择性烟碱受体拮抗剂。

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