Stochastic hybrid modeling of protein recruitment to sites of DNA damage
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Σιδέρης, Εμμανουήλ
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Abstract
Computational models are used for simulation of biological processes in order to verify a hypothesis or to better describe and understand complex biological phenomena. Combined with quantitative experimental data, computational models allow the extraction of valuable information about interactions that determine biological function at the level of molecules, cells, organisms or populations. Aim of this project is the modeling of protein recruitment in specific regions in the nucleus, as a response of DNA damage. When DNA lesions occur, special proteins are accumulating in the region in order to identify and repair the lesion and coordinate cellular response. Here, a stochastic hybrid model is constructed, capable to simulate the protein accumulation in a specified region of the nucleus. This is achieved through the use of a three-dimensional ellipsoid model of the nucleus, into which proteins are modeled as point particles whose movement obeys stochastic hybrid equations. Main element in the model is the appearance of additional binding sites for the proteins in a predefined region in the nucleus, through increased immobilization probability in the region at some specified time during the simulation. This thesis is divided in two parts: Firstly, by using the model the most important parameters and conditions affecting the protein accumulation are investigated. In the second part model results are compared with experimental data. Observation of the cellular response to DNA damage is allowed through the use of functional microscopy experiments. By using image analysis, quantitative data regarding the accumulation of multiple proteins in time can be obtained. Comparing experimental data and in silico results elucidates the kinetic properties of the proteins taking part in DNA damage response and provide quantitative information about the nature of the interactions in different conditions. This comparison is achieved by constructing a parameter identification method, through which theoretical parameters are calculated for different experiments based on the aforementioned microscopy data.
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Keywords
Stochastic hybrid modeling, Switching diffusion, Protein recruitment, DNA damage, Particle based model, Protein accumulation, DNA damage response