Literature DB >> 26986290

Initial condition of stochastic self-assembly.

Jason K Davis1, Suzanne S Sindi1.   

Abstract

The formation of a stable protein aggregate is regarded as the rate limiting step in the establishment of prion diseases. In these systems, once aggregates reach a critical size the growth process accelerates and thus the waiting time until the appearance of the first critically sized aggregate is a key determinant of disease onset. In addition to prion diseases, aggregation and nucleation is a central step of many physical, chemical, and biological process. Previous studies have examined the first-arrival time at a critical nucleus size during homogeneous self-assembly under the assumption that at time t=0 the system was in the all-monomer state. However, in order to compare to in vivo biological experiments where protein constituents inherited by a newly born cell likely contain intermediate aggregates, other possibilities must be considered. We consider one such possibility by conditioning the unique ergodic size distribution on subcritical aggregate sizes; this least-informed distribution is then used as an initial condition. We make the claim that this initial condition carries fewer assumptions than an all-monomer one and verify that it can yield significantly different averaged waiting times relative to the all-monomer condition under various models of assembly.

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Year:  2016        PMID: 26986290     DOI: 10.1103/PhysRevE.93.022109

Source DB:  PubMed          Journal:  Phys Rev E        ISSN: 2470-0045            Impact factor:   2.529


  2 in total

Review 1.  How and why to build a mathematical model: A case study using prion aggregation.

Authors:  Mikahl Banwarth-Kuhn; Suzanne Sindi
Journal:  J Biol Chem       Date:  2020-01-31       Impact factor: 5.157

2.  Generalizing a mathematical model of prion aggregation allows strain coexistence and co-stability by including a novel misfolded species.

Authors:  Paul Lemarre; Laurent Pujo-Menjouet; Suzanne S Sindi
Journal:  J Math Biol       Date:  2018-08-16       Impact factor: 2.259

  2 in total

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