Insights into the variability of nucleated amyloid polymerization by a minimalistic model of stochastic protein assembly

Eugène, Sarah and Xue, Wei-Feng and Robert, Philippe and Doumic, Marie (2016) Insights into the variability of nucleated amyloid polymerization by a minimalistic model of stochastic protein assembly. The Journal of Chemical Physics, 144 (17). p. 175101. ISSN 0021-9606. (doi:https://doi.org/10.1063/1.4947472) (Full text available)

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Abstract

Self-assembly of proteins into amyloid aggregates is an important biological phenomenon associated with human diseases such as Alzheimer’s disease. Amyloid brils 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 di erential 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 o ers a new perspective and paves the way for a new and e cient approach on extracting vital information regarding the key initial events of amyloid formation.

Item Type: Article
Subjects: Q Science
Q Science > QA Mathematics (inc Computing science)
Q Science > QC Physics
Q Science > QD Chemistry
Q Science > QP Physiology (Living systems) > QP517 Biochemistry
Divisions: Faculties > Sciences > School of Biosciences
Depositing User: Wei-Feng Xue
Date Deposited: 04 May 2016 12:08 UTC
Last Modified: 17 Jan 2017 10:16 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/55226 (The current URI for this page, for reference purposes)
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