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转甲状腺素淀粉样变性病中早期蛋白质聚集的随机主方程。

Stochastic master equation for early protein aggregation in the transthyretin amyloid disease.

机构信息

School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, Shaanxi, China.

出版信息

Sci Rep. 2020 Jul 24;10(1):12437. doi: 10.1038/s41598-020-69319-x.

Abstract

It is significant to understand the earliest molecular events occurring in the nucleation of the amyloid aggregation cascade for the prevention of amyloid related diseases such as transthyretin amyloid disease. We develop chemical master equation for the aggregation of monomers into oligomers using reaction rate law in chemical kinetics. For this stochastic model, lognormal moment closure method is applied to track the evolution of relevant statistical moments and its high accuracy is confirmed by the results obtained from Gillespie's stochastic simulation algorithm. Our results show that the formation of oligomers is highly dependent on the number of monomers. Furthermore, the misfolding rate also has an important impact on the process of oligomers formation. The quantitative investigation should be helpful for shedding more light on the mechanism of amyloid fibril nucleation.

摘要

理解淀粉样蛋白聚集级联成核过程中最早发生的分子事件对于预防淀粉样相关疾病(如转甲状腺素淀粉样变性病)具有重要意义。我们使用化学动力学中的反应速率定律为单体聚合形成低聚物开发了化学主方程。对于这种随机模型,对数正态矩闭合方法被应用于跟踪相关统计矩的演变,其通过 Gillespie 的随机模拟算法得到的结果得到了高精度的验证。我们的结果表明,低聚物的形成高度依赖于单体的数量。此外,错误折叠速率对低聚物形成过程也有重要影响。这种定量研究应该有助于深入了解淀粉样纤维成核的机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c09a/7381670/c50b05c7d843/41598_2020_69319_Fig1_HTML.jpg

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