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用于评估呼吸药物在人肺泡巨噬细胞中的细胞摄取程度和溶酶体隔离的体外和计算机模拟工具。

In Vitro and in Silico Tools To Assess Extent of Cellular Uptake and Lysosomal Sequestration of Respiratory Drugs in Human Alveolar Macrophages.

作者信息

Ufuk Ayşe, Assmus Frauke, Francis Laura, Plumb Jonathan, Damian Valeriu, Gertz Michael, Houston J Brian, Galetin Aleksandra

机构信息

Centre for Applied Pharmacokinetic Research, School of Health Sciences, University of Manchester , Manchester, U.K.

Respiratory and Allergy Clinical Research Facility, University Hospital of South Manchester , Manchester, U.K.

出版信息

Mol Pharm. 2017 Apr 3;14(4):1033-1046. doi: 10.1021/acs.molpharmaceut.6b00908. Epub 2017 Mar 20.

DOI:10.1021/acs.molpharmaceut.6b00908
PMID:28252969
Abstract

Accumulation of respiratory drugs in human alveolar macrophages (AMs) has not been extensively studied in vitro and in silico despite its potential impact on therapeutic efficacy and/or occurrence of phospholipidosis. The current study aims to characterize the accumulation and subcellular distribution of drugs with respiratory indication in human AMs and to develop an in silico mechanistic AM model to predict lysosomal accumulation of investigated drugs. The data set included 9 drugs previously investigated in rat AM cell line NR8383. Cell-to-unbound medium concentration ratio (K) of all drugs (5 μM) was determined to assess the magnitude of intracellular accumulation. The extent of lysosomal sequestration in freshly isolated human AMs from multiple donors (n = 5) was investigated for clarithromycin and imipramine (positive control) using an indirect in vitro method (±20 mM ammonium chloride, NHCl). The AM cell parameters and drug physicochemical data were collated to develop an in silico mechanistic AM model. Three in silico models differing in their description of drug membrane partitioning were evaluated; model (1) relied on octanol-water partitioning of drugs, model (2) used in vitro data to account for this process, and model (3) predicted membrane partitioning by incorporating AM phospholipid fractions. In vitro K ranged >200-fold for respiratory drugs, with the highest accumulation seen for clarithromycin. A good agreement in K was observed between human AMs and NR8383 (2.45-fold bias), highlighting NR8383 as a potentially useful in vitro surrogate tool to characterize drug accumulation in AMs. The mean K of clarithromycin (81, CV = 51%) and imipramine (963, CV = 54%) were reduced in the presence of NHCl by up to 67% and 81%, respectively, suggesting substantial contribution of lysosomal sequestration and intracellular binding in the accumulation of these drugs in human AMs. The in vitro data showed variability in drug accumulation between individual human AM donors due to possible differences in lysosomal abundance, volume, and phospholipid content, which may have important clinical implications. Consideration of drug-acidic phospholipid interactions significantly improved the performance of the in silico models; use of in vitro K obtained in the presence of NHCl as a surrogate for membrane partitioning (model (2)) captured the variability in clarithromycin and imipramine K observed in vitro and showed the best ability to predict correctly positive and negative lysosomotropic properties. The developed mechanistic AM model represents a useful in silico tool to predict lysosomal and cellular drug concentrations based on drug physicochemical data and system specific properties, with potential application to other cell types.

摘要

尽管呼吸药物在人肺泡巨噬细胞(AMs)中的蓄积对治疗效果和/或磷脂沉积症的发生有潜在影响,但在体外和计算机模拟方面尚未得到广泛研究。本研究旨在表征具有呼吸适应症的药物在人AMs中的蓄积和亚细胞分布,并建立一个计算机模拟机制性AMs模型,以预测所研究药物的溶酶体蓄积。数据集包括先前在大鼠AMs细胞系NR8383中研究过的9种药物。测定所有药物(5μM)的细胞与未结合培养基浓度比(K),以评估细胞内蓄积的程度。使用间接体外方法(±20 mM氯化铵,NHCl),对来自多个供体(n = 5)的新鲜分离的人AMs中克拉霉素和丙咪嗪(阳性对照)的溶酶体隔离程度进行了研究。整理AMs细胞参数和药物理化数据,以建立一个计算机模拟机制性AMs模型。评估了三种在药物膜分配描述上不同的计算机模拟模型;模型(1)依赖于药物的正辛醇-水分配,模型(2)使用体外数据来解释这一过程,模型(3)通过纳入AMs磷脂组分来预测膜分配。呼吸药物的体外K值范围>200倍,克拉霉素的蓄积最高。在人AMs和NR8383之间观察到K值有良好的一致性(偏差2.45倍),突出了NR8383作为表征药物在AMs中蓄积的潜在有用体外替代工具。在存在NHCl的情况下,克拉霉素(平均K = 81,CV = 51%)和丙咪嗪(平均K = 963,CV = 54%)的平均K值分别降低了高达67%和81%,表明溶酶体隔离和细胞内结合对这些药物在人AMs中的蓄积有很大贡献。体外数据显示,由于溶酶体丰度、体积和磷脂含量可能存在差异,个体人AMs供体之间的药物蓄积存在变异性,这可能具有重要的临床意义。考虑药物与酸性磷脂的相互作用显著提高了计算机模拟模型的性能;使用在存在NHCl的情况下获得的体外K值作为膜分配的替代值(模型(2))捕捉了体外观察到的克拉霉素和丙咪嗪K值的变异性,并显示出正确预测阳性和阴性溶酶体趋向性特性的最佳能力。所开发的机制性AMs模型是一种有用的计算机模拟工具,可根据药物理化数据和系统特定特性预测溶酶体和细胞内药物浓度,具有应用于其他细胞类型的潜力。

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