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Stoichiometries and affinities of interacting proteins from concentration series of solution scattering data: decomposition by least squares and quadratic optimization

机译:溶液散射数据浓度序列中相互作用蛋白的化学计量和亲和力:最小二乘分解和二次优化

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摘要

In studying interacting proteins, complementary insights are provided by analyzing both the association model (the stoichiometry and affinity constants of the intermediate and final complexes) and the quaternary structure of the resulting complexes. Many current methods for analyzing protein interactions either give a binary answer to the question of association and no information about quaternary structure or at best provide only part of the complete picture. Presented here is a method to extract both types of information from X-ray or neutron scattering data for a series of equilibrium mixtures containing the initial components at different concentrations. The method determines the association pathway and constants, along with the scattering curves of the individual members of the mixture, so as to best explain the scattering data for the mixtures. The derived curves then enable reconstruction of the intermediate and final complexes. Using simulated solution scattering data for four hetero-oligomeric complexes with different structures, molecular weights and association models, it is demonstrated that this method accurately determines the simulated association model and scattering profiles for the initial components and complexes. Recognizing that experimental mixtures contain static contaminants and nonspecific complexes with the lowest affinities (inter-particle interference) as well as the desired specific complex(es), a new analytical method is also employed to extend this approach to evaluating the association models and scattering curves in the presence of static contaminants, testing both a nonparticipating monomer and a large homo-oligomeric aggregate. It is demonstrated that the method is robust to both random noise and systematic noise from such contaminants, and the treatment of nonspecific complexes is discussed. Finally, it is shown that this method is applicable over a large range of weak association constants typical of specific but transient protein–protein complexes.
机译:在研究相互作用的蛋白质时,通过分析关联模型(中间和最终复合物的化学计量和亲和常数)和所得复合物的四级结构,可以提供互补的见解。当前用于分析蛋白质相互作用的许多方法要么给出了关联问题的二元答案,而没有关于四级结构的信息,或者充其量仅提供了完整图片的一部分。这里介绍的是一种从X射线或中子散射数据中提取两种类型信息的方法,用于一系列包含不同浓度初始成分的平衡混合物。该方法确定了缔合途径和常数,以及混合物中各个成分的散射曲线,从而最好地解释了混合物的散射数据。然后,导出的曲线可以重建中间和最终复合物。使用具有不同结构,分子量和缔合模型的四个杂合-低聚物配合物的模拟溶液散射数据,证明了该方法可以准确地确定初始组分和配合物的模拟缔合模型和散射曲线。认识到实验混合物含有静态污染物和亲和力最低(粒子间干扰)的非特异性配合物,以及所需的特异性配合物,因此还采用了一种新的分析方法来将该方法扩展为评估缔合模型和散射曲线在静态污染物的存在下,同时测试非参与单体和大型均聚物-低聚物。证明了该方法对于来自此类污染物的随机噪声和系统噪声均具有鲁棒性,并讨论了非特异性复合物的处理。最后,表明该方法适用于大范围的特定但短暂的蛋白质-蛋白质复合物的弱缔合常数。

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