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从核磁共振数据建模蛋白质聚集动力学。

Modeling Protein Aggregation Kinetics from NMR Data.

作者信息

Tugarinov Vitali, Torricella Francesco, Ghosh Shreya, Clore G Marius

机构信息

Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892-0520, USA.

Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892-0520, USA.

出版信息

J Mol Biol. 2025 Jun 9:169269. doi: 10.1016/j.jmb.2025.169269.

Abstract

We provide an overview of the practical aspects of using NMR spectroscopy to follow the time course of protein fibril formation (aggregation) and quantitatively model the kinetics of aggregation processes. Following a brief survey of the theoretical foundations of the kinetics of protein aggregation and its inhibition, the modeling of aggregation kinetics, from data acquired by a series of fast two-dimensional H-N correlation NMR spectra, is described. Examples are drawn from our recent NMR-based studies of (1) the aggregation kinetics of a pathogenic huntingtin exon-1 protein whose fibrillization in neurons is responsible for Huntington's disease, and (2) the kinetics of amyloid β42 fibril formation and the mechanism of its inhibition by the chaperone Hsp104.

摘要

我们概述了使用核磁共振波谱法追踪蛋白质纤维形成(聚集)的时间进程并对聚集过程动力学进行定量建模的实际操作。在简要综述蛋白质聚集动力学及其抑制的理论基础之后,描述了如何根据一系列快速二维氢-氮相关核磁共振波谱获取的数据对聚集动力学进行建模。实例取自我们最近基于核磁共振的研究,包括:(1)致病性亨廷顿蛋白外显子1的聚集动力学,其在神经元中的纤维化是导致亨廷顿舞蹈病的原因;(2)淀粉样β42纤维形成的动力学及其被伴侣蛋白Hsp104抑制的机制。

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