Simulating a faulty mechanism of protein folding in the pathogenesis of familial Parkinson’s disease

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. Pathogenic mutations may directly induce abnormal protein conformations or compromise the ability of the cellular machinery to detect and degrade misfolded proteins. Although the recent explosion in the rate of discovery of genetic defects 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 quantitative models for in silico experiments, that can help the researchers either to elucidate important and still elusive aspects of the Parkinson’s disease or to design new wet-experiments. Here we present three stochastic models of a faulty mechanism of protein re-folding and degradation of misfolded proteins. Our models are specified in biochemical stochastic π-calculus and are based on what is currently known about the genetic mutations causing PD. The expressive capabilities of this formalism in the description of parallel and competive nature of biochemical interactions make it particularly suitable for modeling the intricate mechanism of proteins folding, refolding and eventually degradation. Furthermore, the simulation results point out those kinetic quantitative parameters, whose variations lead to significant changes in the capability of the system to react to the accumulation of dangerous proteins.