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A rule-based model of Clathrin Mediated Endocytosis: Gaining a better understanding of Parkinson's Disease

Research output: Contribution to conferencePoster

Original languageEnglish
Publication statusPublished - 5 Jul 2015
EventInternational Synthetic and Systems Biology Summer School: Biology meets Engineering and Computer Science - Hotel Villa Diodoro Congress Center, Taormina, Italy
Duration: 5 Jul 20159 Jul 2015
http://www.taosciences.it/ssbss2015/#home

Other

OtherInternational Synthetic and Systems Biology Summer School
Abbreviated titleSSBSS 2015
CountryItaly
CityTaormina
Period5/07/159/07/15
Internet address

Abstract

Parkinson’s Disease (PD) is the second most common neurodegenerative disease in the modern world. Nevertheless we are far from understanding disease causing dysfunctions and identifying early disease stages.
Through a variety of experimental and analytical approaches a variety of proteins are known to be associated with Parkinson’s Disease. There is experimental evidence for about 30 well-known proteins to cause PD or play a crucial role in the disease progression. An additional 200 proteins have been implicated in the disease based on Genome Wide Association Studies and Microarray Analysis.
Based on network analysis studies we see that PD-causing proteins are enriched in specific synaptic departments, such as the vesicle cycle. We identified clathrin mediated endocytosis (CME) as a potentially measurable variable to distinguish healthy against disease conditions. CME is a process that regulates (synaptic) plasma membrane turnover, e.g. internalization of receptors and lipids, as well as the uptake of extracellular material like neurotransmitters, nutrients and growth factors. As a pre-synaptic pathway it hosts many proteins that trigger the
development of Parkinson’s Disease and is linked to further PD-causing proteins. Hence we are highly interested in gaining further insights into this process.
Due to the large number of proteins required for an extended model of CME, rule-based modelling was chosen. Based on the formulation of rather generic rules instead of very specific equations, this allows us to build a dynamic model of a larger system. It avoids the combinatorial explosion, often occurring when considering growing protein models and is easily extendible when needed.
We can currently model part of the endocytosis process and are looking forward to simulating a more complete system in the near future. Preliminary insights into the endocytosis process and aberrations under disease conditions will be presented and give hope to further advances in the understanding of Parkinson's Disease.

ID: 39643921