Structural identifiability of equilibrium ligand-binding parameters.
Structural identifiability of equilibrium ligand-binding parameters.
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DOI：
10.1085/jgp.201611702
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发表时间：
2017-01
期刊：
影响因子：
--
通讯作者：
Aldrich RW
中科院分区：
文献类型：
--
作者：
Middendorf TR;Aldrich RW
配体-蛋白质相互作用的精确数学描述由于无法实验测量亲和力和协作性而受到阻碍，尽管这些参数可以从激动剂结合模型中估计出来。米登多夫和奥尔德里奇提出了一种方法来确定以这种方式估计的参数的准确性。要了解蛋白质与其配体的相互作用，需要了解分子性质，例如结合部位的亲和力，以及一个部位的结合对其他部位结合的影响(协作性)。这些属性不能直接测量，通常通过将绑定数据与包含这些量作为参数的模型进行拟合来估计。在这项研究中，我们提出了一种通用的方法来回答这些参数是否可识别的关键问题(即它们的估计是否准确和唯一)。在参数估计不是唯一的情况下，我们的分析提供了对不可识别的根本原因的洞察。因此，这种方法可以作为正确设计和分析蛋白质-配体结合实验的指南。我们表明，对于所有只由双分子缔合反应组成的模型，平衡总结合关系可以简化为保守的数学形式，对于由结合平衡和构象平衡的任意组合组成的所有模型，平衡总结合关系可以简化为相关的保守形式。这种规范的数学结构意味着结合关系的普遍参数化，对于具有任何数量结合位点的蛋白质来说，这几乎与任何物理上合理的结合模型一致。矩阵代数方法被用来证明这些通用参数集在结构上是可识别的(SI；即在无噪声数据的条件下可识别)。在Middendorf和Aldrich(2017)的配文中，提出了一种评估和理解影响这些SI参数集的实际可识别性(即，在真实噪声数据条件下的可识别性)的一般方法。J.Gen.Physiol.Https://doi.org/10.1085/jgp.201611703).
Precise mathematical descriptions of ligand–protein interactions are hindered by the inability to experimentally measure affinity and cooperativity, although these parameters can be estimated from agonist binding models. Middendorf and Aldrich present a method to determine the accuracy of parameters estimated in this way. Understanding the interactions of proteins with their ligands requires knowledge of molecular properties, such as binding site affinities and the effects that binding at one site exerts on binding at other sites (cooperativity). These properties cannot be measured directly and are usually estimated by fitting binding data with models that contain these quantities as parameters. In this study, we present a general method for answering the critical question of whether these parameters are identifiable (i.e., whether their estimates are accurate and unique). In cases in which parameter estimates are not unique, our analysis provides insight into the fundamental causes of nonidentifiability. This approach can thus serve as a guide for the proper design and analysis of protein–ligand binding experiments. We show that the equilibrium total binding relation can be reduced to a conserved mathematical form for all models composed solely of bimolecular association reactions and to a related, conserved form for all models composed of arbitrary combinations of binding and conformational equilibria. This canonical mathematical structure implies a universal parameterization of the binding relation that is consistent with virtually any physically reasonable binding model, for proteins with any number of binding sites. Matrix algebraic methods are used to prove that these universal parameter sets are structurally identifiable (SI; i.e., identifiable under conditions of noiseless data). A general approach for assessing and understanding the factors governing practical identifiability (i.e., the identifiability under conditions of real, noisy data) of these SI parameter sets is presented in the companion paper by Middendorf and Aldrich (2017. J. Gen. Physiol. https://doi.org/10.1085/jgp.201611703).
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