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Online Journal of Bioinformatics ©
In silico experiments on
a faulty ubiquitin-proteasome system in the
pathogenesis of Parkinson’s disease
Paola Lecca
Microsoft Research -
ABSTRACT
Lecca P, In silico
experiments on a faulty ubiquitin-proteasome system in the pathogenesis of Parkinson’s disease, Online J
Bioinformatics, 9 (1):30-43, 2008. A growing body of evidence suggests that the
accumulation of misfolded proteins in brain tissues
is a crucial event in the Parkinson’s disease neurodegeneration.
Both pathogenic genetic mutations and the exposure to environmental toxins may
induce abnormal protein conformations or compromise the ability of the cellular
machinery (mainly the chaperones and ubiquitin-proteasome
systems) to detect and degrade misfolded proteins.
Although the recent explosion in the rate of discovery of genetic defects and
environmental factors linked to Parkinson’s disease (PD) have provided tangible
clues to the neurobiology of the disorder, they have provided neither direct
explanation for the disease process or its key biochemical mechanism. The aim
of the work is to provide computational models for in silico
experiments, that can enable the medical researchers to
formulate new hypotheses for elucidating some important and still elusive
aspects of the Parkinson’s disease and for designing new wet experiments
to test them. Here we present three stochastic models of a faulty mechanism of
protein re-folding and degradation of misfolded
proteins: (i) a model describing the effects of
environmental stress factors on the processing of misfolded
proteins, and (ii) two models of genetic Parkinson due to the mutations of α-synuclein and parkin. Our models
are specified in biochemical stochastic π-calculus and are based on what
is currently known about the genetic mutations and environmental stress causing
PD. The expressive capabilities of this formalism in the description of
parallel and competitive nature of biochemical interactions make it
particularly suitable for modeling the intricate mechanism of proteins folding,
re-folding and eventually degradation. Furthermore, the simulation results
point out those kinetic quantitative parameters (e. g. reaction rate
coefficients and the number of available chaperons), whose
variations lead to significant changes in the capability of the system to react
to the accumulation of dangerous proteins.
Keywords:
stochastic π-calculus, kinetic analysis, Parkinson’s disease, parkin, ubiquitin, chaperones.
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