Insights into the variability of nucleated amyloid polymerization by a minimalistic model of stochastic protein assembly
Insights into the variability of nucleated amyloid polymerization by a minimalistic model of stochastic protein assembly
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DOI：
10.1063/1.4947472
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发表时间：
2016-05-07
影响因子：
4.4
通讯作者：
Doumic, Marie
中科院分区：
文献类型：
--
作者：
Eugene, Sarah;Xue, Wei-Feng;Doumic, Marie
蛋白质自组装成淀粉样蛋白聚集体是与阿尔茨海默病等人类疾病相关的重要生物学现象。淀粉样原纤维在生物材料的纳米工程中也具有潜在的应用。淀粉样蛋白组装的动力学显示出指数生长期，之后是滞后期，其持续时间可变，如在批量实验和模拟小体积细胞的实验中所见。在这里，为了研究淀粉样蛋白组装滞后期观察到的变异性的起源和性质，目前确定性成核依赖性机制无法解释这一变化，我们制定了一种新的随机最小模型，尽管其简单，但能够描述淀粉样蛋白生长曲线的特征。然后，我们求解模型的随机微分方程，并给出有核聚集过程的样本生长轨迹的中心极限定理的数学证明。这些结果为我们的简单模型提供了渐近描述，从中得出能够描述和预测有核淀粉样蛋白组装变异性的封闭形式分析结果。我们还展示了我们的结果的应用，以概念上友好且清晰的方式为实验提供信息。我们的模型提供了一个新的视角，并为提取有关淀粉样蛋白形成的关键初始事件的重要信息的新的有效方法铺平了道路。由 AIP 出版社出版。
Self-assembly of proteins into amyloid aggregates is an important biological phenomenon associated with human diseases such as Alzheimer's disease. Amyloid fibrils also have potential applications in nano-engineering of biomaterials. The kinetics of amyloid assembly show an exponential growth phase preceded by a lag phase, variable in duration as seen in bulk experiments and experiments that mimic the small volumes of cells. Here, to investigate the origins and the properties of the observed variability in the lag phase of amyloid assembly currently not accounted for by deterministic nucleation dependent mechanisms, we formulate a new stochastic minimal model that is capable of describing the characteristics of amyloid growth curves despite its simplicity. We then solve the stochastic differential equations of our model and give mathematical proof of a central limit theorem for the sample growth trajectories of the nucleated aggregation process. These results give an asymptotic description for our simple model, from which closed form analytical results capable of describing and predicting the variability of nucleated amyloid assembly were derived. We also demonstrate the application of our results to inform experiments in a conceptually friendly and clear fashion. Our model offers a new perspective and paves the way for a new and efficient approach on extracting vital information regarding the key initial events of amyloid formation. Published by AIP Publishing.