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首页> 外文期刊>Molecular pharmaceutics >Estimation of Drug Binding to Brain Tissue: Methodology and in Vivo Application of a Distribution Assay in Brain Polar Lipids
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Estimation of Drug Binding to Brain Tissue: Methodology and in Vivo Application of a Distribution Assay in Brain Polar Lipids

机译:药物与脑组织结合的估计:方法和在脑极性脂质中的分布测定的体内应用。

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The unbound drug concentration-effect relationship in brain is a key aspect in CNS drug discovery and development. In this work, we describe an in vitro high-throughput distribution assay between an aqueous buffer and a microemulsion of porcine brain polar lipids (BPL). The derived distribution coefficient LogD(BPL), was applied to the prediction of unbound drug concentrations in brain (C-u,C-b) and nonspecific binding to brain tissue. The in vivo relevance of the new assay was assessed for a large set of proprietary drug candidates and CNS drugs by (1) comparing observed compound concentrations in rat CSF with Cu,b calculated using the LogD(BPL) assay in combination with total drug brain concentrations, (2) comparing C-u,C-b derived from LogD(BPL), and total drug brain concentrations to C-u,C-b estimated using in vitro P-glycoprotein efflux ratio data and unbound drug plasma levels, and (3) comparing tissue nonspecific binding data from human brain autoradiography studies for 17 PET tracer candidates to distribution in BPL. In summary, the LogD(BPL) assay provides a predicted drug fraction unbound in brain tissue that is nearly identical to brain homogenate equilibrium dialysis with an estimation of in vivo C-u,C-b that is superior to LogD in octanol. LogD(BPL) complements the approach for predicting C-u,C-b based on in vitro P-glycoprotein efflux ratio and in vivo unbound plasma concentration and stands as a fast and cost-effective tool for nonspecific brain binding optimization of PET ligand candidates.
机译:脑中未结合的药物浓度-效应关系是中枢神经系统药物发现和开发的关键方面。在这项工作中,我们描述了水性缓冲液和猪脑极性脂质(BPL)微乳液之间的体外高通量分布测定。导出的分布系数LogD(BPL)用于预测大脑中未结合药物的浓度(C-u,C-b)和与脑组织的非特异性结合。通过(1)比较使用LogD(BPL)分析与总药物大脑结合计算得出的大鼠CSF和Cu,b中观察到的化合物浓度,评估了新方法在体内大量候选专利和中枢神经系统药物的体内相关性浓度,(2)比较使用LogD(BPL)衍生的Cu,Cb,以及使用体外P-糖蛋白流出比数据和未结合药物血浆水平估算的总药物脑浓度与Cu,Cb,以及(3)比较组织非特异性结合数据从人脑X射线照相术研究中选择了17种PET示踪剂,然后分配给BPL。总之,LogD(BPL)分析提供了在脑组织中未结合的预测药物分数,该分数与脑匀浆平衡透析几乎相同,而体内C-u,C-b的估算值优于在辛醇中的LogD。 LogD(BPL)补充了基于体外P糖蛋白流出比和体内未结合血浆浓度预测C-u,C-b的方法,并且是PET配体候选物非特异性脑结合优化的快速且经济高效的工具。

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