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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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