Approximately half of all proteins are associated with ordered lipid aggregates such as the plasma membrane. These molecules are involved in an array of processes critical for the maintenance of life, including signaling, environmental sensing, import/export, homeostasis, and cellular structure.
Despite the crucial role that membrane-associated proteins play, we know less about them than we do of their soluble counterparts. This is due primarily to technical limitations of the standard techniques employed for producing and studying biological macromolecules, which often work best for samples in which the protein is soluble in aqueous buffer at high concentrations. Due to their ability to interact with hydrophobic lipids, membrane-associated proteins frequently pose complications to the researcher in this sample production phase. Recent advances in techniques and scientific methods (driven by a strong desire to elucidate the workings of the membrane systems) have led to a rapid expansion in our knowledge; both the basic information needed to effectively work with these types of molecules as well as an increase in our biochemical dataset of their functions.
This is not to say that obtaining data on membrane-associated proteins is now facile. It is critical to leverage the appropriate tools in order to extract the maximum amount of information from the system being studied. As such, this document describes the course of my own work into several membrane-associated proteins. In all of these studies I employed computational methods such as molecular modeling to guide the work. The in silico predictions were useful in increasing protein production, allowed for comparisons across a family of similar proteins, and suggested experimental lines of inquiry. At the same time, disagreements between simulations and in vitro data reinforced the necessity of obtaining experimental results.
The first three chapters of this dissertaion detail my work with G Protein-Coupled Receptors (GPCRs). These integral, polytopic transmembrane polypeptides are one of the largest superfamilies of proteins and are central players in signal transduction across a lipid bilayer. I describe the design and initial generation steps of a ligand binding analog of the Tachykinin NK1 Receptor which is more amenable to structural analysis. In this case a homology model of NK1 was used during the analog design phase. Distance information from this model was applied to determine the lengths of linker sequences to include between ligand binding segments of the receptor. The partial genes for these segments were then synthesised and combined to create the full analog gene. We then expressed, purified, and characterized the protein. I also describe my investigations into the activation of the unfolded protein response in Saccharomyces cerevisiae when the NK1 receptor is heterologously expressed. We found that overexpression of NK1 in yeast induced the Unfolded Protein Response, in contrast to the Adenosine A2A receptor which did not.
The next four chapters deal with my experiments involving a family of peripheral membrane associated proteins, the Phospholipases A2 (PLA2). I describe the generation of a homology model of the Platelet Activating Factor Acetyl Hydrolase Type 2 (PAFAH2) based on a template structure recently solved in our lab. This model was used to help guide our mutagenesis experiments to further understand the activation of the protein under conditions of oxidative stress, as well as to draw comparisons with the structure of the related plasma PAFAH.
I then move on to cover work on the small secreted PLA2 family. This project primarily focused on elucidation of the causes of inhibitor specificity between the human group V and group X proteins. In order to facilitate model building we developed software tools which combined disulfide bond definition, heteroatom inclusion, structurally influenced alignments, and scoring of the produced models. For both of the PLA2 projects we found that these methods were necessary in order to generate acceptable homology models, and were superior to “black-box” automated algorithms. For the sPLA 2s, the homology model of the human Group V protein allowed us to compare the features of this protein with other physiologically relevant family members in order to connect structural features with biological function.
Once again, the common thread throughout the work described in this dissertation is the augmentation of in vitro experiments with in silico calculations. This application of predictive tools acts as a means of maximizing research time and optimizing the use of the limited material produced in the laboratory.
|Advisor:||Bahnson, Brian J.|
|Commitee:||Polenova, Tatyana, Robinson, Anne S., Rozovsky, Sharon|
|School:||University of Delaware|
|Department:||Department of Chemistry and Biochemistry|
|School Location:||United States -- Delaware|
|Source:||DAI-B 70/07, Dissertation Abstracts International|
|Keywords:||Computational modeling, Crystallography, G-protein coupled receptors, Membrane proteins, Phospholipase, Protein purification|
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