Computational approaches to analyse and predict small molecule transport and distribution at cellular and subcellular levels.
Computational approaches to analyse and predict small molecule transport and distribution at cellular and subcellular levels.
复制标题
分析和预测细胞和亚细胞水平下的小分子传输和分布的计算方法。
DOI：
10.1002/bdd.1879
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发表时间：
2014-01
影响因子：
2.1
通讯作者：
Rosania, Gus R.
中科院分区：
文献类型：
--
作者：
Min, Kyoung Ah;Zhang, Xinyuan;Yu, Jing-yu;Rosania, Gus R.
定量构效关系（Quantitative structure-activity relationship， QSAR）研究和机械数学建模方法已被独立用于分析和预测小分子化学制剂在生物体内的转运和分布。这两种计算方法都有助于解释测量小分子化学试剂在体外和体内运输特性的实验。然而，基于细胞的机制药代动力学模型在指导设计探测小分子运输现象背后的分子途径的实验方面特别有用。与QSAR模型不同，机制模型可以从微观到宏观水平进行整合，以分析从细胞内细胞器到整个器官的小分子化学剂的时空动态，远远超出了模型所基于的实验和训练数据集。基于微分方程的机制模型也可以与其他基于微分方程的生化网络或信号通路的系统生物学模型相结合。尽管旨在预测药物运输和分布的数学建模方法的起源和发展独立于系统生物学，但我们建议将基于机械细胞的药物运输和分布计算模型纳入系统生物学建模框架是推进系统药理学研究的合乎逻辑的下一步。
Quantitative structure-activity relationship (QSAR) studies and mechanistic mathematical modeling approaches have been independently employed for analyzing and predicting the transport and distribution of small molecule chemical agents in living organisms. Both of these computational approaches have been useful to interpret experiments measuring the transport properties of small molecule chemical agents, in vitro and in vivo. Nevertheless, mechanistic cell-based pharmacokinetic models have been especially useful to guide the design of experiments probing the molecular pathways underlying small molecule transport phenomena. Unlike QSAR models, mechanistic models can be integrated from microscopic to macroscopic levels, to analyze the spatiotemporal dynamics of small molecule chemical agents from intracellular organelles to whole organs, well beyond the experiments and training data sets upon which the models are based. Based on differential equations, mechanistic models can also be integrated with other differential equations-based systems biology models of biochemical networks or signaling pathways. Although the origin and evolution of mathematical modeling approaches aimed at predicting drug transport and distribution has occurred independently from systems biology, we propose that the incorporation of mechanistic cell-based computational models of drug transport and distribution into a systems biology modeling framework is a logical next-step for the advancement of systems pharmacology research.
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影响因子：
4
作者：
Chen, Vivien Y.;Rosania, Gus R.
通讯作者：
Rosania, Gus R.
影响因子：
4.9
作者：
Baik, Jason;Stringer, Kathleen A.;Rosania, Gus R.
通讯作者：
Rosania, Gus R.
影响因子：
9.8
作者：
BALAZ, S;WIESE, M;SEYDEL, JK
通讯作者：
SEYDEL, JK
影响因子：
3.7
作者：
Chen, Vivien Y.;Posada, Maria M.;Rosania, Gus R.
通讯作者：
Rosania, Gus R.
影响因子：
3.8
作者：
BALAZ, S;WIESE, M;SEYDEL, JK
通讯作者：
SEYDEL, JK