Protein aggregation is a key process in the development of many neurodegenerative disorders, including dementias such as Alzheimer's disease. Significant progress has been made in understanding the molecular mechanisms of aggregate formation in pure buffer systems, much of which was enabled by the development of integrated rate laws that allowed for mechanistic analysis of aggregation kinetics. However, in order to translate these findings into disease-relevant conclusions and to make predictions about the effect of potential alterations to the aggregation reactions by the addition of putative inhibitors, the current models need to be extended to account for the altered situation encountered in living systems. In particular, in vivo, the total protein concentrations typically do not remain constant and aggregation-prone monomers are constantly being produced but also degraded by cells. Here, we build a theoretical model that explicitly takes into account monomer production, derive integrated rate laws and discuss the resulting scaling laws and limiting behaviours. We demonstrate that our models are suited for the aggregation-prone Huntington's disease-associated peptide HttQ45 utilizing a system for continuous in situ monomer production and the aggregation of the tumour suppressor protein P53. The aggregation-prone HttQ45 monomer was produced through enzymatic cleavage of a larger construct in which a fused protein domain served as an internal inhibitor. For P53, only the unfolded monomers form aggregates, making the unfolding a rate-limiting step which constitutes a source of aggregation-prone monomers. The new model opens up possibilities for a quantitative description of aggregation in living systems, allowing for example the modelling of inhibitors of aggregation in a dynamic environment of continuous protein synthesis.

中文翻译：

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动力学模型揭示蛋白质生产和聚集的相互作用

蛋白质聚集是许多神经退行性疾病（包括阿尔茨海默病等痴呆症）发展的关键过程。在理解纯缓冲系统中聚集体形成的分子机制方面已经取得了重大进展，其中大部分是通过开发集成速率定律来实现的，该定律允许对聚集动力学进行机械分析。然而，为了将这些发现转化为与疾病相关的结论，并预测添加假定抑制剂对聚集反应的潜在改变的影响，当前的模型需要扩展以考虑生活中遇到的改变情况。系统。特别是，在体内，总蛋白浓度通常不会保持恒定，并且容易聚集的单体不断产生，但也会被细胞降解。在这里，我们建立了一个理论模型，明确考虑单体生产，推导综合速率定律并讨论由此产生的缩放定律和限制行为。我们证明，我们的模型适用于易于聚集的亨廷顿病相关肽 HttQ45，利用连续原位单体生产和肿瘤抑制蛋白 P53 聚集的系统。易于聚集的 HttQ45 单体是通过酶裂解较大的构建体产生的，其中融合蛋白结构域充当内部抑制剂。对于 P53，只有未折叠的单体才会形成聚集体，从而使未折叠成为限速步骤，从而成为易于聚集的单体的来源。新模型为定量描述生命系统中的聚集开辟了可能性，例如允许在连续蛋白质合成的动态环境中对聚集抑制剂进行建模。