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基于溶液散射数据浓度系列的相互作用蛋白质的化学计量学和亲和力:通过最小二乘法和二次优化进行分解

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

作者信息

Chandola Himanshu, Williamson Tim E, Craig Bruce A, Friedman Alan M, Bailey-Kellogg Chris

机构信息

Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA.

Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA.

出版信息

J Appl Crystallogr. 2014 May 10;47(Pt 3):899-914. doi: 10.1107/S1600576714005913. eCollection 2014 Jun 1.

Abstract

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.

摘要

在研究相互作用的蛋白质时,通过分析缔合模型(中间体和最终复合物的化学计量和亲和常数)以及所得复合物的四级结构,可以提供互补的见解。目前许多分析蛋白质相互作用的方法要么对缔合问题给出二元答案,而不提供关于四级结构的信息,要么最多只提供完整图景的一部分。本文介绍了一种从X射线或中子散射数据中提取这两种信息的方法,该数据来自一系列含有不同浓度初始组分的平衡混合物。该方法确定缔合途径和常数,以及混合物中各个成员的散射曲线,以便最好地解释混合物的散射数据。然后,导出的曲线能够重建中间体和最终复合物。使用具有不同结构、分子量和缔合模型的四种异源寡聚复合物的模拟溶液散射数据,证明了该方法能够准确确定初始组分和复合物的模拟缔合模型和散射轮廓。认识到实验混合物中包含静态污染物和具有最低亲和力的非特异性复合物(粒子间干扰)以及所需的特异性复合物,还采用了一种新的分析方法将该方法扩展到评估存在静态污染物时的缔合模型和散射曲线,同时测试了一种不参与的单体和一种大型同源寡聚聚集体。结果表明,该方法对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方法。最后,结果表明该方法适用于特定但短暂的蛋白质-蛋白质复合物典型的大范围弱缔合常数。

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