Proteins are the engines and building blocks of life. They are long chains of amino acids, built up using 20 different amino acids and folded to create structures of great complexity. Proteins participate in cell regulation, function and maintenance. They have structural roles and information signaling roles. Their functionality is sequence and structure driven and thus structural errors can have severe consequences. Significant scientific efforts are being devoted to discover protein interaction pathways as well as to ascertain and predict protein structures. The complexity of proteins and the cell environment make the simulation of the protein folding extremely demanding on computational resources. This complexity means that even when an experimentalist can use gene alteration and other advanced techniques, it is not a trivial task to determine cause and effect, especially in living cells. It is not simple to draw conclusions from animal experiments to humans.
In my dissertation, I will present a new computational approach that enables the prediction of protein susceptibility to forming a stable left hand beta helical (LHBH) structure—a structure suspected of facilitating abnormal aggregation and creation of fibrils associated with prion diseases. My computational algorithm does not try to directly simulate the physical forces nor is it based on bioinformatics data rather I use a physical motivated energy function to evaluate structure viability and thus allow fast protein structure prediction. Other computational tools currently available are either ineffective or too slow for such tasks. In the second part of my dissertation I present a new aggregation model and computational approach to create aggregation phase and kinetic diagrams. My model is designed to better represent the in vivo environment. I use it to explore the possibility that in Alzheimer’s disease (AD), the prion protein (PrPc), a membrane-bound protein, plays an important role in the formation of aggregates associated with the disease and is maybe a link between extra-cellular and intra-cellular AD aggregates. The aggregation phase diagrams and the in vivo simulation approach are important new tools that can help compare and interpret experimental results, understand aggregate formation process, and design experiments.
|Advisor:||Cox, Daniel L.|
|Commitee:||Chrutchfield, James P., Singh, Rajiv R.|
|School:||University of California, Davis|
|School Location:||United States -- California|
|Source:||DAI-B 73/01, Dissertation Abstracts International|
|Keywords:||Aggregation kinetics, Alzheimer's disease, Amyloid-beta, Protein aggregation, Protein structure|
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