Matching Items (3)
Filtering by

Clear all filters

153462-Thumbnail Image.png
Description
Calcitonin Gene-Related Peptide (CGRP) is an intrinsically disordered protein

that has no regular secondary structure, but plays an important role in vasodilation and pain transmission in migraine. Little is known about the structure and dynamics of the monomeric state of CGRP or how CGRP is able to function in the cell,

Calcitonin Gene-Related Peptide (CGRP) is an intrinsically disordered protein

that has no regular secondary structure, but plays an important role in vasodilation and pain transmission in migraine. Little is known about the structure and dynamics of the monomeric state of CGRP or how CGRP is able to function in the cell, despite the lack of regular secondary structure. This work focuses characterizing the non-local structural and dynamical properties of the CGRP monomer in solution, and understanding how these are affected by the sequence and the solution environment. The unbound, free state of CGRP is measured using a nanosecond laser-pump spectrophotometer, which allows measuring the end-to-end distance (a non-local structural property) and the rate of end-to-end contact formation (intra-chain diffusional dynamics). The data presented in this work show that electrostatic interactions strongly modulate the structure of CGRP, and that peptide-solvent interactions are sequence and charge dependent and can have a significant effect on the internal dynamics of the peptide. In the last few years migraine research has shifted focus to disrupting the CGRP-receptor pathway through the design of pharmacological drugs that bind to either CGRP or its receptor, inhibiting receptor activation and therefore preventing or reducing the frequency of migraine attacks. Understanding what types of intra- and inter-chain interactions dominate in CGRP can help better design drugs that disrupt the binding of CGRP to its receptor.
ContributorsSizemore, Sara (Author) / Vaiana, Sara (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Ros, Robert (Committee member) / Lindsay, Stuart (Committee member) / Ozkan, Sefika (Committee member) / Arizona State University (Publisher)
Created2015
151211-Thumbnail Image.png
Description
CpG methylation is an essential requirement for the normal development of mammals, but aberrant changes in the methylation can lead to tumor progression and cancer. An in-depth understanding of this phenomenon can provide insights into the mechanism of gene repression. We present a study comparing methylated DNA and normal DNA

CpG methylation is an essential requirement for the normal development of mammals, but aberrant changes in the methylation can lead to tumor progression and cancer. An in-depth understanding of this phenomenon can provide insights into the mechanism of gene repression. We present a study comparing methylated DNA and normal DNA wrt its persistence length and contour length. Although, previous experiments and studies show no difference between the physical properties of the two, the data collected and interpreted here gives a different picture to the methylation phenomena and its effect on gene silencing. The study was extended to the artificially reconstituted chromatin and its interactions with the methyl CpG binding proteins were also probed.
ContributorsKaur, Parminder (Author) / Lindsay, Stuart (Thesis advisor) / Ros, Robert (Committee member) / Tao, Nongjian (Committee member) / Vaiana, Sara (Committee member) / Beckenstein, Oliver (Committee member) / Arizona State University (Publisher)
Created2012
155215-Thumbnail Image.png
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