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基于单分子荧光共振能量转移技术的未折叠和内在无序蛋白质的精确转移效率、距离分布及集合体

Accurate Transfer Efficiencies, Distance Distributions, and Ensembles of Unfolded and Intrinsically Disordered Proteins From Single-Molecule FRET.

作者信息

Holmstrom Erik D, Holla Andrea, Zheng Wenwei, Nettels Daniel, Best Robert B, Schuler Benjamin

机构信息

Department of Biochemistry, University of Zurich, Zurich, Switzerland.

Department of Biochemistry, University of Zurich, Zurich, Switzerland.

出版信息

Methods Enzymol. 2018;611:287-325. doi: 10.1016/bs.mie.2018.09.030. Epub 2018 Nov 16.

Abstract

Intrinsically disordered proteins (IDPs) sample structurally diverse ensembles. Characterizing the underlying distributions of conformations is a key step toward understanding the structural and functional properties of IDPs. One increasingly popular method for obtaining quantitative information on intramolecular distances and distributions is single-molecule Förster resonance energy transfer (FRET). Here we describe two essential elements of the quantitative analysis of single-molecule FRET data of IDPs: the sample-specific calibration of the single-molecule instrument that is required for determining accurate transfer efficiencies, and the use of state-of-the-art methods for inferring accurate distance distributions from these transfer efficiencies. First, we illustrate how to quantify the correction factors for instrument calibration with alternating donor and acceptor excitation measurements of labeled samples spanning a wide range of transfer efficiencies. Second, we show how to infer distance distributions based on suitably parameterized simple polymer models, and how to obtain conformational ensembles from Bayesian reweighting of molecular simulations or from parameter optimization in simplified coarse-grained models.

摘要

内在无序蛋白(IDP)呈现出结构多样的集合体。表征其潜在的构象分布是理解IDP结构和功能特性的关键一步。一种越来越流行的获取分子内距离和分布定量信息的方法是单分子荧光共振能量转移(FRET)。在这里,我们描述了IDP单分子FRET数据定量分析的两个基本要素:确定准确转移效率所需的单分子仪器的样品特异性校准,以及使用先进方法从这些转移效率推断准确的距离分布。首先,我们说明了如何通过对跨越广泛转移效率范围的标记样品进行交替供体和受体激发测量来量化仪器校准的校正因子。其次,我们展示了如何基于适当参数化的简单聚合物模型推断距离分布,以及如何从分子模拟的贝叶斯重加权或简化粗粒度模型中的参数优化获得构象集合体。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d13/8018263/ed179d72a632/nihms-1626252-f0001.jpg

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