Classical structural identifiability methodology applied to low-dimensional dynamic systems in receptor theory.
Classical structural identifiability methodology applied to low-dimensional dynamic systems in receptor theory.
复制标题
经典结构可识别性方法应用于受体理论中的低维动态系统。
DOI：
10.1007/s10928-023-09870-y
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发表时间：
2024
影响因子：
2.5
通讯作者：
White C
中科院分区：
文献类型：
--
作者：
White C
数学建模已成为药理学分析的关键工具，有助于理解细胞信号传导的动力学和量化配体-受体相互作用。受体理论中的常微分方程（ODE）模型可用于使用时程数据来参数化这种相互作用，但需要注意感兴趣的参数的理论可识别性。可识别性分析是许多生物建模工作中经常被忽视的一步。在本文中，我们介绍了结构可识别性分析（SIA）的受体理论领域的应用三个经典的SIA方法（传递函数，泰勒级数和相似性变换）的配体-受体结合模型的生物学意义（单配体和Motulsky-Mahan竞争结合在单体，和最近提出的一个单一的配体结合在受体二聚体的模型）。获得了新的结果，表明可识别的参数为一个单一的时间过程中的Motulsky-Mahan结合和二聚化受体结合。重要的是，我们进一步考虑可以进行的实验的组合，以克服不可识别性的问题，以确保工作的实用性。三个SIA方法通过一个教程式的方法，使用详细的计算，这表明该方法是易于处理的低维常微分方程模型。
Mathematical modelling has become a key tool in pharmacological analysis, towards understanding dynamics of cell signalling and quantifying ligand-receptor interactions. Ordinary differential equation (ODE) models in receptor theory may be used to parameterise such interactions using timecourse data, but attention needs to be paid to the theoretical identifiability of the parameters of interest. Identifiability analysis is an often overlooked step in many bio-modelling works. In this paper we introduce structural identifiability analysis (SIA) to the field of receptor theory by applying three classical SIA methods (transfer function, Taylor Series and similarity transformation) to ligand-receptor binding models of biological importance (single ligand and Motulsky-Mahan competition binding at monomers, and a recently presented model of a single ligand binding at receptor dimers). New results are obtained which indicate the identifiable parameters for a single timecourse for Motulsky-Mahan binding and dimerised receptor binding. Importantly, we further consider combinations of experiments which may be performed to overcome issues of non-identifiability, to ensure the practical applicability of the work. The three SIA methods are demonstrated through a tutorial-style approach, using detailed calculations, which show the methods to be tractable for the low-dimensional ODE models.