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一种针对疾病相关蛋白组装中序列聚集关系的动力学方法。

A kinetic approach to the sequence-aggregation relationship in disease-related protein assembly.

机构信息

Forschungszentrum Jülich GmbH Institute of Complex Systems: Structural Biochemistry (ICS-6), 52425 Jülich, Germany.

出版信息

J Phys Chem B. 2014 Jan 30;118(4):1003-11. doi: 10.1021/jp412648u. Epub 2014 Jan 17.

DOI:10.1021/jp412648u
PMID:24401100
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3908877/
Abstract

It is generally accepted that oligomers of aggregating proteins play an important role in the onset of neurodegenerative diseases. While in silico aggregation studies of full length amyloidogenic proteins are computationally expensive, the assembly of short protein fragments derived from these proteins with similar aggregating properties has been extensively studied. In the present work, molecular dynamics simulations are performed to follow peptide aggregation on the microsecond time scale. By defining aggregation states, we identify transition networks, disconnectivity graphs, and first passage time distributions to describe the kinetics of the assembly process. This approach unravels differences in the aggregation into hexamers of two peptides with different primary structures. The first is GNNQQNY, a hydrophilic fragment from the prion protein Sup35, and the second is KLVFFAE, a fragment from amyloid-β protein, with a hydrophobic core delimited by two charged amino acids. The assembly of GNNQQNY suggests a mechanism of monomer addition, with a bias toward parallel peptide pairs and a gradual increase in the amount of β-strand content. For KLVFFAE, a mechanism involving dimers rather than monomers is revealed, involving a generally higher β-strand content and a transition toward a larger number of antiparallel peptide pairs during the rearrangement of the hexamer. The differences observed for the aggregation of the two peptides suggests the existence of a sequence-aggregation relationship.

摘要

普遍认为,聚集蛋白的低聚物在神经退行性疾病的发病中起着重要作用。虽然全长淀粉样蛋白蛋白的计算机模拟聚集研究计算成本很高,但这些蛋白的类似聚集特性的短蛋白片段的组装已经得到了广泛研究。在本工作中,进行了分子动力学模拟,以在微秒时间尺度上跟踪肽的聚集。通过定义聚集状态,我们确定了过渡网络、不连通图和首次通过时间分布,以描述组装过程的动力学。这种方法揭示了两种具有不同一级结构的肽在六聚体中的聚集差异。第一个是 GNNQQNY,它是朊病毒蛋白 Sup35 的亲水片段,第二个是 KLVFFAE,它是淀粉样-β蛋白的片段,其疏水核心由两个带电荷的氨基酸限定。GNNQQNY 的组装表明了单体添加的机制,其偏向于平行肽对,并且β-折叠含量逐渐增加。对于 KLVFFAE,揭示了涉及二聚体而不是单体的机制,涉及一般更高的β-折叠含量,并且在六聚体的重排过程中,平行肽对的数量逐渐增加。两种肽的聚集所观察到的差异表明存在序列聚集关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/f05972d3d8ce/emss-56281-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/273cb687486a/emss-56281-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/df0d89de6352/emss-56281-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/cf384f51edca/emss-56281-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/656d6e69998a/emss-56281-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/67aef86560aa/emss-56281-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/f05972d3d8ce/emss-56281-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/273cb687486a/emss-56281-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/df0d89de6352/emss-56281-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/cf384f51edca/emss-56281-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/656d6e69998a/emss-56281-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/67aef86560aa/emss-56281-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d2f/3908877/f05972d3d8ce/emss-56281-f0006.jpg

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