Inference of Joint Conformational Distributions from Separately Acquired Experimental Measurements.

Inference of Joint Conformational Distributions from Separately Acquired Experimental Measurements.
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DOI:
10.1021/acs.jpclett.0c03623
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发表时间:
2021-02-18
期刊:
The journal of physical chemistry letters
影响因子:
--
通讯作者:
Kasson PM
Kasson PM
中科院分区:
其他
文献类型:
--
作者:
Hays JM;Boland E;Kasson PM

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柔性蛋白质在许多生物过程中起着至关重要的作用。然而,确定它们的完整构象系综是极其困难的,因为这需要关于蛋白质自由度的异质性的详细知识。基于标记的实验,如鹿,在研究柔性蛋白质方面非常有用,因为它们提供了关于异质性的分布数据。这些实验通常是单独执行的,因此有关分布之间相关性的信息会丢失。我们开发了一种在分子动力学精化中使用非平衡功估计来恢复关联信息的方法。我们在一个简单模型上对该方法进行了测试,该模型的真实联合分布是已知的,它成功地恢复了真实的联合分布。我们还将我们的方法应用于蛋白质Synaxin-1a,其中它丢弃了物理上不可信的构象。因此,我们的方法提供了一种在构象系综的单独实验测量中恢复关联结构的方法,并精炼了由此产生的结构系综。
Flexible proteins serve vital roles in a multitude of biological processes. However, determining their full conformational ensembles is extremely difficult because this requires detailed knowledge about the heterogeneity of the protein’s degrees of freedom. Label-based experiments such as DEER are very useful in studying flexible proteins, as they provide distributional data on heterogeneity. These experiments are typically performed separately, so information about correlation between distributions is lost. We have developed a method to recover correlation information using non-equilibrium work estimates in molecular dynamics refinement. We tested this method on a simple model of an alternating-access transporter for which the true joint distributions are known, and it successfully recovered the true joint distribution. We also applied our method to the protein syntaxin-1a, where it discarded physically implausible conformations. Our method thus provides a way to recover correlation structure in separate experimental measurements of conformational ensembles and refines the resulting structural ensemble.
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