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Description
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.,

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.
ContributorsButler, Brandon Mac (Author) / Ozkan, S. Banu (Thesis advisor) / Vaiana, Sara (Committee member) / Ghirlanda, Giovanna (Committee member) / Ros, Robert (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Traditionally, allostery is perceived as the response of a catalytic pocket to perturbations induced by binding at another distal site through the interaction network in a protein, usually associated with a conformational change responsible for functional regulation. Here, I utilize dynamics-based metrics, Dynamic Flexibility Index and Dynamic Coupling Index to

Traditionally, allostery is perceived as the response of a catalytic pocket to perturbations induced by binding at another distal site through the interaction network in a protein, usually associated with a conformational change responsible for functional regulation. Here, I utilize dynamics-based metrics, Dynamic Flexibility Index and Dynamic Coupling Index to provide insight into how 3D network of interactions wire communications within a protein and give rise to the long-range dynamic coupling, thus regulating key allosteric interactions. Furthermore, I investigate its role in modulating protein function through mutations in evolution. I use Thioredoxin and β-lactamase enzymes as model systems, and show that nature exploits "hinge-shift'' mechanism, where the loss in rigidity of certain residue positions of a protein is compensated by reduced flexibility of other positions, for functional evolution. I also developed a novel approach based on this principle to computationally engineer new mutants of the promiscuous ancestral β-lactamase (i.e., degrading both penicillin and cephatoxime) to exhibit specificity only towards penicillin with a better catalytic efficiency through population shift in its native ensemble.I investigate how allosteric interactions in a protein can regulate protein interactions in a cell, particularly focusing on E. coli ribosome. I describe how mutations in a ribosome can allosterically change its associating with magnesium ions, which was further shown by my collaborators to distally impact the number of biologically active Adenosine Triphosphate molecules in a cell, thereby, impacting cell growth. This allosteric modulation via magnesium ion concentrations is coined, "ionic allostery''. I also describe, the role played by allosteric interactions to regulate information among proteins using a simplistic toy model of an allosteric enzyme. It shows how allostery can provide a mechanism to efficiently transmit information in a signaling pathway in a cell while up/down regulating an enzyme’s activity.
The results discussed here suggest a deeper embedding of the role of allosteric interactions in a protein’s function at cellular level. Therefore, bridging the molecular impact of allosteric regulation with its role in communication in cellular signaling can provide further mechanistic insights of cellular function and disease development, and allow design of novel drugs regulating cellular functions.
ContributorsModi, Tushar (Author) / Ozkan, Sefika (Thesis advisor) / Beckstein, Oliver (Committee member) / Vaiana, Sara (Committee member) / Ros, Robert (Committee member) / Arizona State University (Publisher)
Created2020