IJPAM: Volume 93, No. 6 (2014)

SIZE DISTRIBUTION OF AMYLOID FIBRILS.
MATHEMATICAL MODELS AND EXPERIMENTAL DATA

S. Prigent$^1$, H.W. Haffaf$^2$, H.T. Banks$^3$,
M. Hoffmann$^4$, H. Rezaei$^5$, M. Doumic$^6$
$^{1,2,6}$Inria, Institut National de Recherche en Informatique et Automatique
Rocquencourt, FRANCE
$^{1,2,6}$Pierre et Marie Curie University
Paris-Diderot University
CNRS UMR 7598, Paris, FRANCE
$^3$Center for Research in Scientific Computation (CRSC)
North Carolina State University
Raleigh, N.C., USA
$^4$CEREMADE (Centre de REcherche en MAthématique de la DEcision)
CNRS-UMR 7534 and CREST
University Paris-Dauphine
Paris, FRANCE
$^5$Institut National de Recherche Agronomique
Jouy-en-Josas, FRANCE


Abstract. More than twenty types of proteins can adopt misfolded conformations, which can co-aggregate into amyloid fibrils, and are related to pathologies such as Alzheimer’s disease. This article surveys mathematical models for aggregation chain reactions, and discuss the ability to use them to understand amyloid distributions. Numerous reactions have been proposed to play a role in their aggregation kinetics, though the relative importance of each reaction in vivo is unclear: these include activation steps, with nucleation compared to initiation, disaggregation steps, with depolymerization compared to fragmentation, and additional processes such as filament coalescence or secondary nucleation. We have statistically analysed the shape of the size distribution of prion fibrils, with the specific example of truncated data due to the experimental technique (electron microscopy). A model of polymerization and depolymerization succeeds in explaining this distribution. It is a very plausible scheme though, as evidenced in the review of other mathematical models, other types of reactions could also give rise to the same type of distributions.

Received: April 22, 2014

AMS Subject Classification: 92D25, 34E99, 62G07, 62P10.

Key Words and Phrases: protein aggregation, PrP fiber, Becker-Döring system, statistical test, kernel density estimation

Download paper from here.




DOI: 10.12732/ijpam.v93i6.10 How to cite this paper?

Source:
International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2014
Volume: 93
Issue: 6
Pages: 845 - 878

CC BY This work is licensed under the Creative Commons Attribution International License (CC BY).