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一种用于拥挤条件下无序蛋白质的粗粒度模型。

A coarse-grained model for disordered proteins under crowded conditions.

作者信息

Rauh Arriën Symon, Tesei Giulio, Lindorff-Larsen Kresten

机构信息

Structural Biology and NMR Laboratory, Linderstrøm-Lang Centre for Protein Science, Department of Biology, University of Copenhagen, Copenhagen, Denmark.

出版信息

Protein Sci. 2025 Aug;34(8):e70232. doi: 10.1002/pro.70232.

Abstract

Macromolecular crowding may strongly affect the dynamics and function of proteins, with intrinsically disordered proteins being particularly sensitive to their crowded environment. To understand the influences of crowding on chain compaction and phase separation (PS) behavior of disordered proteins, both experiments with synthetic crowders-like polyethylene glycol (PEG) and ficoll-and theoretical models and molecular simulation approaches have been applied. Here, we developed a residue-based coarse-grained model for PEG that is compatible with the protein CALVADOS model. To achieve this, we optimized model parameters by comparing simulations with experimental data on single-chain PEG and on PEG-induced compaction of disordered proteins. With our model we show how titrations of PEG can be used to quantify PS propensities of proteins that are not prone to phase separate strongly. We illustrate this for both variants of the low-complexity domain of hnRNPA1 (A1-LCD), and for wild-type and a redesigned variant of α-synuclein. Notably, we observe that the PEG crowding response changes between charge patterning variants of α-synuclein, which is not the case for the variants that vary the number of aromatic residues in the A1-LCD. We expect that our model will be useful for the interpretation of crowding experiments with disordered proteins, and we envisage it to be a starting point for explorations of proteins with weak propensities to phase separate.

摘要

大分子拥挤效应可能会强烈影响蛋白质的动力学和功能,其中内在无序蛋白质对其拥挤环境尤为敏感。为了理解拥挤对无序蛋白质的链压缩和相分离(PS)行为的影响,人们既采用了类似聚乙二醇(PEG)和菲可葡聚糖等合成拥挤剂的实验方法,也运用了理论模型和分子模拟方法。在此,我们开发了一种基于残基的PEG粗粒化模型,该模型与蛋白质CALVADOS模型兼容。为此,我们通过将模拟结果与单链PEG以及PEG诱导的无序蛋白质压缩的实验数据进行比较,对模型参数进行了优化。利用我们的模型,我们展示了如何通过滴定PEG来量化那些不易强烈相分离的蛋白质的PS倾向。我们以hnRNPA1低复杂性结构域(A1-LCD)的两种变体,以及α-突触核蛋白的野生型和重新设计变体为例进行了说明。值得注意的是,我们观察到α-突触核蛋白的电荷模式变体之间的PEG拥挤响应有所变化,而A1-LCD中芳香族残基数量不同的变体则并非如此。我们预计我们的模型将有助于解释无序蛋白质的拥挤实验,并且设想它将成为探索弱相分离倾向蛋白质的起点。

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