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首页> 外文期刊>Journal of Molecular Biology >Atomic-level characterization of the ensemble of the Abeta(1-42) monomer in water using unbiased molecular dynamics simulations and spectral algorithms.
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Atomic-level characterization of the ensemble of the Abeta(1-42) monomer in water using unbiased molecular dynamics simulations and spectral algorithms.

机译:使用无偏分子动力学模拟和光谱算法对水中Abeta(1-42)单体的集合进行原子级表征。

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Abeta(1-42) is the highly pathologic isoform of amyloid-beta, the peptide constituent of fibrils and neurotoxic oligomers involved in Alzheimer's disease. Recent studies on the structural features of Abeta in water have suggested that the system can be described as an ensemble of distinct conformational species in fast exchange. Here, we use replica exchange molecular dynamics (REMD) simulations to characterize the conformations accessible to Abeta42 in explicit water solvent, under the ff99SB force field. Monitoring the correlation between J-coupling((3)J(H(N))(H(alpha))) and residual dipolar coupling (RDC) data calculated from the REMD trajectories to their experimental values, as determined by NMR, indicates that the simulations converge towards sampling an ensemble that is representative of the experimental data after 60 ns/replica of simulation time. We further validate the converged MD-derived ensemble through direct comparison with (3)J(H(N))(H(alpha)) and RDC experimental data. Our analysis indicates that the ff99SB-derived REMD ensemble can reproduce the experimental J-coupling values with high accuracy and further provide good agreement with the RDC data. Our results indicate that the peptide is sampling a highly diverse range of conformations: by implementing statistical learning techniques (Laplacian eigenmaps, spectral clustering, and Laplacian scores), we are able to obtain an otherwise hidden structure in the complex conformational space of the peptide. Using these methods, we characterize the peptide conformations and extract their intrinsic characteristics, identify a small number of different conformations that characterize the whole ensemble, and identify a small number of protein interactions (such as contacts between the peptide termini) that are the most discriminative of the different conformations and thus can be used in designing experimental probes of transitions between such molecular states. This is a study of an important intrinsically disordered peptide system that provides an atomic-level description of structural features and interactions that are relevant during the early stages of the oligomerization and fibril nucleation pathways.
机译:Abeta(1-42)是淀粉样蛋白β的高度病理性同工型,淀粉样蛋白是原纤维和参与阿尔茨海默氏病的神经毒性寡聚体的肽成分。对水中Abeta结构特征的最新研究表明,该系统可描述为快速交换中独特构象物种的集合。在这里,我们使用副本交换分子动力学(REMD)模拟来表征在ff99SB力场下,显性水溶剂中Abeta42可访问的构象。监测由REMD轨迹计算出的J耦合((3)J(H(N))(Hα))和残余偶极耦合(RDC)数据与其实验值之间的相关性,这由NMR确定,表明模拟趋向于采样60 ns /模拟时间副本后的代表实验数据的整体。我们通过与(3)J(H(N))(Hα)和RDC实验数据进行直接比较,进一步验证了融合MD的集成体。我们的分析表明,由ff99SB衍生的REMD集成可以高精度地再现实验J耦合值,并进一步与RDC数据提供良好的一致性。我们的结果表明,该肽正在采样范围广泛的构象:通过实施统计学习技术(拉普拉斯特征图,谱聚类和拉普拉斯分数),我们能够在该肽的复杂构象空间中获得其他隐藏结构。使用这些方法,我们可以表征肽构象并提取其内在特征,鉴定出少量表征整个集合体的不同构象,并鉴定出最有区别的少量蛋白质相互作用(例如肽末端之间的接触)构象的不同,因此可用于设计此类分子状态之间跃迁的实验探针。这是对重要的内在无序的肽系统的研究,该系统提供了在寡聚化和原纤维成核途径早期相关的结构特征和相互作用的原子级描述。

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