Skip to main content
Kent Academic Repository

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

Eugène, Sarah, Xue, Wei-Feng, Robert, Philippe, 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). Article Number 175101. ISSN 0021-9606. (doi:10.1063/1.4947472) (KAR id:55226)

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
DOI/Identification number: 10.1063/1.4947472
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: Divisions > Division of Natural Sciences > Biosciences
Depositing User: Wei-Feng Xue
Date Deposited: 04 May 2016 12:08 UTC
Last Modified: 09 Dec 2022 05:40 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/55226 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.