Protein-protein interactions are of vital importance to the cell as they mediate the assembly of protein complexes that carry out diverse biological functions. Many proteins involved in cellular signaling are built by the combinatorial use of peptide recognition modules (PRMs), which are small protein domains that bind to their cognate ligands by recognizing short linear peptide motifs. Thousands of PRMs are found in nature, requiring improved methods to better elucidate their molecular determinants of binding and to allow accurate mapping of their interaction networks. In this thesis, I describe the development and application of phage-displayed peptide libraries to map the binding specificities of two common PRMs. First, I generated specificity profiles for 82 C. elegans and human PDZ domains that could be organized into a specificity map. The map revealed that PDZ domains have far greater substrate sequence specificity than previously believed, providing significant insights into the relationships between PDZ structure and specificity, and allowing specificity prediction for uncharacterized domains. My results were used to predict both endogenous and pathogenic PDZ interactions. This analysis revealed that viruses have evolved ligands that specifically mimic PDZ domains to subvert host cell immunity.
Second, I analyzed the binding specificity for the SH3 domain family in S. cerevisae. I found that, like PDZ domains, SH3 domains have binding specificities that are more detailed than the conventional classification system. The phage-derived specificity profiles were combined with data from oriented peptide and yeast two-hybrid screening to generate a highly accurate SH3 domain interaction network. Given the prominent role of SH3 domains in endocytosis, the SH3 domain interaction data was used to predict the dynamic localization of several uncharacterized endocytosis proteins, which was subsequently confirmed by cell-based assays.
The application of the techniques described here to other PRM families will significantly improve protein interaction maps for signaling pathways, which will illuminate our understanding of the cell circuitry, allow the use of PRMs as general affinity reagent and detection tools, and guide the development of small molecule inhibitors that mimic their peptide ligands for therapeutic intervention.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/19302 |
| Date | 03 March 2010 |
| Creators | Tonikian, Raffi |
| Contributors | Boone, Charles |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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