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 Online Journal of Bioinformatics © 

 Volume 9 (1):30-43, 2008.

In silico experiments on a faulty ubiquitin-proteasome system in the pathogenesis of Parkinsonís disease


Paola Lecca


Microsoft Research - University of Trento Centre for Computational and System Biology, piazza Manci 17, 38100 Povo (Trento), Italy




Lecca P, In silico experiments on a faulty ubiquitin-proteasome system in  the pathogenesis of Parkinsonís disease, Onl J Bioinform., 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 Parkinsonís 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 Parkinsonís 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 Parkinsonís 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, Parkinsonís disease, parkin, ubiquitin, chaperones.