Cells use a variety of different mechanisms to sense and respond to the constantly changing environment. Single celled organisms use signaling pathways to find food, escape toxins, and protect themselves in dangerous or overcrowded environments. The failure of cell signaling in these organisms usually leads to the death of the cell. In a multi-celled organism, individual cells rely on signaling pathways to cooperate with the rest of the organism. A failure in cell to cell signaling in higher organisms may lead to the brief survival of the cell but the eventual failure and death of the organism as a whole. We chose to apply various methods to study cell signaling and communication in both prokaryotic and eukaryotic organisms. The first two approaches we took to this problem were entirely computational. We developed parameters for phosphorylated amino acids and used these parameters to predict structural changes as a function of phosphorylation. In addition, we showed that both phosphate charge and the geometry by which this phosphate interacts with other residues determine the energy gained or lost as a result of this interaction. Next, we joined computation and experiment to successfully predict agonists and antagonists for a G-protein coupled receptor. In a follow up study, we used the information gained on the G-protein coupled receptor to investigate selectivity among a set of similar receptors from different mammals. In the final section of this work, we use a mixture of computation and experiment to show that two component signaling pathways do not interfere with one another in vivo. We then apply this knowledge to deconstruct the bacterial chemotaxis pathway into two separate, orthogonal signaling systems.
|Advisor:||Jacobson, Matthew P., Voigt, Christopher A.|
|Commitee:||Miller, Susan M.|
|School:||University of California, San Francisco|
|Department:||Pharmaceutical Sciences and Pharmacogenomics|
|School Location:||United States -- California|
|Source:||DAI-B 69/12, Dissertation Abstracts International|
|Subjects:||Microbiology, Bioinformatics, Biophysics|
|Keywords:||Computational structure prediction, Phosphorylation, Synthetic biology, Two-component signaling systems|
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