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abstract: Proteins are essential for most biological processes that constitute life. The function of a protein is encoded within its 3D folded structure, which is determined by its sequence of amino acids. A variation of a single nucleotide in the DNA during transcription (nSNV) can alter the amino acid sequence (i.e., a mutation in the protein sequence), which can adversely impact protein function and sometimes cause disease. These mutations are the most prevalent form of variations in humans, and each individual genome harbors tens of thousands of nSNVs that can be benign (neutral) or lead to disease. The primary way to assess the impact of nSNVs on function is through evolutionary approaches based on positional amino acid conservation. These approaches are largely inadequate in the regime where positions evolve at a fast rate. We developed a method called dynamic flexibility index (DFI) that measures site-specific conformational dynamics of a protein, which is paramount in exploring mechanisms of the impact of nSNVs on function. In this thesis, we demonstrate that DFI can distinguish the disease-associated and neutral nSNVs, particularly for fast evolving positions where evolutionary approaches lack predictive power. We also describe an additional dynamics-based metric, dynamic coupling index (DCI), which measures the dynamic allosteric residue coupling of distal sites on the protein with the functionally critical (i.e., active) sites. Through DCI, we analyzed 200 disease mutations of a specific enzyme called GCase, and a proteome-wide analysis of 75 human enzymes containing 323 neutral and 362 disease mutations. In both cases we observed that sites with high dynamic allosteric residue coupling with the functional sites (i.e., DARC spots) have an increased susceptibility to harboring disease nSNVs. Overall, our comprehensive proteome-wide analysis suggests that incorporating these novel position-specific conformational dynamics based metrics into genomics can complement current approaches to increase the accuracy of diagnosing disease nSNVs. Furthermore, they provide mechanistic insights about disease development. Lastly, we introduce a new, purely sequence-based model that can estimate the dynamics profile of a protein by only utilizing coevolution information, eliminating the requirement of the 3D structure for determining dynamics. / Dissertation/Thesis / Doctoral Dissertation Physics 2016

Rhomboids are a family of intramembrane serine proteases that cleave transmembrane protein substrates within the lipid membrane. They are involved in a wide range of biological processes, including signal transduction, parasite invasion, bacterial quorum sensing and apoptosis. While previous X-ray crystal structures and functional studies have provided some detailed insights into the mechanism of intramembrane hydrolysis, it is still not clear how the transmembrane substrate can gain access into the active site from the lipid environment. While several modes of action have been suggested, one hypothesis proposes a lateral movement of the fifth transmembrane helix, causing a displacement that would allow transmembrane substrates to enter the rhomboid active site. A powerful method that has the potential to yield insights into rhomboid dynamics is solution NMR; however, the large size of rhomboid protease samples has complicated conventional methods typically used to assess protein structure and dynamics. ¹⁹F NMR could allow the study of rhomboid conformational dynamics by providing a simplified spectrum with high sensitivity to changes in local chemical environments. In this thesis various methods of ¹⁹F incorporation were evaluated for utility in studying rhomboid conformational dynamics, focusing on the GlpG rhomboid from E. coli. First, GlpG samples were prepared with ¹⁹F incorporated into tryptophan sidechains, and 1D ¹⁹F NMR spectra were acquired. While spectra with decent spectral dispersion were obtained, the assignment process was complicated by low signal-to-noise, and multiple changes in the spectrum introduced by the mutation. Chemoselective labelling of cysteine residues with probes containing a trifluoromethyl group was also investigated and found to give rise to well resolved ¹⁹F NMR spectra with promising characteristics. In addition, protocols for incorporation of trifluoromethyl-phenylalanine using unnatural amino acid incorporation at introduced amber codon sites were also explored, since one of the long-term goals of this work is to study ¹⁹F-labelled GlpG in its native lipid environment. For this purpose, some protocol development was also performed to introduce GlpG into lipid nanoparticles using styrene maleic acid co-block polymers. However, low expression yields of trifluoromethyl-phenylalanine-labelled GlpG and the large size of the lipid nanoparticles are not yet compatible with solution NMR. Nonetheless, this thesis lays the groundwork for further development of these samples to allow the future study of conformational exchange of GlpG in native lipid membranes.

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