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浓度依赖的淀粉样β(16-21)淀粉样蛋白核形成的多尺度研究

Multiscale Exploration of Concentration-Dependent Amyloid-β(16-21) Amyloid Nucleation.

机构信息

State Key Laboratory of Chemical Oncogenomics, Guangdong Provincial Key Laboratory of Chemical Genomics, School of Chemical Biology and Biotechnology, Peking University Shenzhen Graduate School, Shenzhen, 518055, China.

Institute of Chemical Biology, Shenzhen Bay Laboratory, Shenzhen, 518132, China.

出版信息

J Phys Chem Lett. 2022 Jun 9;13(22):5009-5016. doi: 10.1021/acs.jpclett.2c00685. Epub 2022 Jun 1.

Abstract

Atomic descriptions of peptide aggregation nucleation remain lacking due to the difficulty of exploring complex configurational spaces on long time scales. To elucidate this process, we develop a multiscale approach combining a metadynamics-based method with cluster statistical mechanics to derive concentration-dependent free energy surfaces of nucleation at near-atomic resolution. A kinetic transition network of nucleation is then constructed and employed to systematically explore nucleation pathways and kinetics through stochastic simulations. This approach is applied to describe Aβ amyloid nucleation, revealing a two-step mechanism involving disordered aggregates at millimolar concentration, and an unexpected mechanism at submillimolar concentrations that exhibits kinetics reminiscent of classical nucleation but atypical pathways involving growing clusters with structured cores wrapped by disordered surface. When this atypical mechanism is operative, critical nucleus size can be reflected by the nucleation reaction order. Collectively, our approach paves the way for a more quantitative and detailed understanding of peptide aggregation nucleation.

摘要

由于难以在长时间尺度上探索复杂的构象空间,肽聚集成核的原子描述仍然缺乏。为了阐明这一过程,我们开发了一种多尺度方法,将基于元动力学的方法与簇统计力学相结合,以在近原子分辨率下推导出与浓度相关的成核自由能面。然后构建了一个成核的动力学转变网络,并通过随机模拟系统地探索成核途径和动力学。该方法应用于描述 Aβ 淀粉样蛋白成核,揭示了涉及毫摩尔浓度下无定形聚集体的两步机制,以及亚毫摩尔浓度下出乎意料的机制,该机制表现出类似于经典成核的动力学,但途径非典型,涉及带有结构化核心的生长簇,被无定形表面包裹。当这种非典型机制起作用时,临界核大小可以反映成核反应级数。总的来说,我们的方法为更定量和详细地理解肽聚集成核铺平了道路。

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