Abstract
A prominent feature of Parkinson's disease (PD) is the loss of dopamine in the striatum, and many therapeutic interventions for the disease are aimed at restoring dopamine signaling. Dopamine signaling includes the synthesis, storage, release, and recycling of dopamine in the presynaptic terminal and activation of pre- and post-synaptic receptors and various downstream signaling cascades. As an aid that might facilitate our understanding of dopamine dynamics in the pathogenesis and treatment in PD, we have begun to merge currently available information and expert knowledge regarding presynaptic dopamine homeostasis into a computational model, following the guidelines of biochemical systems theory. After subjecting our model to mathematical diagnosis and analysis, we made direct comparisons between model predictions and experimental observations and found that the model exhibited a high degree of predictive capacity with respect to genetic and pharmacological changes in gene expression or function. Our results suggest potential approaches to restoring the dopamine imbalance and the associated generation of oxidative stress. While the proposed model of dopamine metabolism is preliminary, future extensions and refinements may eventually serve as an in silico platform for prescreening potential therapeutics, identifying immediate side effects, screening for biomarkers, and assessing the impact of risk factors of the disease.
Highlights
Parkinson’s disease (PD) is the most common neurodegenerative movement disorder, affecting more than 1% of the worldwide population over the age of 65 [1,2]
While PD is a complex, multi-faceted disease, it has been suggested that neurodegeneration is primarily due to the generation of toxic species and to oxidative stress caused by abnormal dopamine metabolism [6,7,8,9]
Steady-State Analysis The model of dopamine metabolism was diagnosed, analyzed, and refined according to the guidelines provided in BST [30]
Summary
Parkinson’s disease (PD) is the most common neurodegenerative movement disorder, affecting more than 1% of the worldwide population over the age of 65 [1,2]. While PD is a complex, multi-faceted disease, it has been suggested that neurodegeneration is primarily due to the generation of toxic species and to oxidative stress caused by abnormal dopamine metabolism [6,7,8,9]. Because loss of dopamine is responsible for the majority of the motor symptoms of PD, treatment options have mostly been based upon restoration of dopamine function by replacement of dopamine precursors, inhibition of degradative enzymes, or dopamine agonists. L-DOPA treatment, which should counteract decreases in dopamine, tends to become ineffective after a while, again demonstrating the complexity of the controlled, adaptive metabolic system. Given the inherent complexity of dopamine dynamics and the redox state of the neuron, a quantitative analysis using mathematical models could enhance our understanding of these complicated processes
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