Summary:
The main objective of Systems Biology is to create mathematical and
computational models allowing to study of the dynamical behavior of biological
systems. In recent years, important findings about the molecular mechanisms
involved in the development of Parkinson’s Disease (PD) appeared in the
literature with key successes having to do with the elucidation of the
contribution of protein alpha-synuclein (ASYN) and the consequences of its
mutation or overexpression. In this Master’s thesis, we take the first steps
towards creating a computational model capable to simulate ASYN overexpression
related dynamical phenomena in the cell and especially those concerning its
oligomerization, the degradation by different proteolytic mechanisms and the
inhibition of those due to pathogenic behavior of this protein. The developed
biomolecular reactions model, which was trained using experimental data,
simulates particularly well the observed phenomena. More importantly though, it
is shown to predict the behavior of the biological system when various
experimental interventions are applied, although no parameter learning
procedure has been used specific to these cases. These results are encouraging
and positive indications for the accuracy of the model, its predictive value,
and its potential to assist the quest for the key mechanisms contributing to
the development of the disease.
Keywords:
Parkinson’s Disease, alpha-synuclein, biochemical networks, modeling, in silico experiments
