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- All Subjects: protein evolution
- Creators: Ros, Robert
Description
One of the most important issues in femtosecond free electron laser X-ray diraction is to reconstruct the 3D charge density of molecule from a mass of diraction snapshots. In order to determine the orientation of single molecule from diraction patterns, we rst determine the moments and products of inertia of this from 2D experiment data (diraction patterns or EM images to obtain the elements of the inertia tensor. If diraction patterns from uniformly random orientations or some preferred orientations are collected, the principal axes of the molecule can be extracted, together with the Euler angles which relate the principal axes of the molecule to the laboratory frame axes. This is achieved by nding the maximum and minimum values for the measured moments from many single-molecule patterns. Simulations for GroEL protein indicates that the calculation of the autocorrelation help eliminate the Poisson noise in Cryo- EM images and can make correct orientation determination. The eect of water jacket surrounding the protein molecule is studied based on molecular dynamics simulation result. The intensities from water and interference is found to suppress those from protein itself. A method is proposed and applied to the simulation data to show the possibility for it to overcome the water background problem. The scattering between Bragg re ections from nanocrystals is used to aid solution of the phase problem. We describe a method for reconstructing the charge density of a typical molecule within a single unit cell, if suciently nely-sampled diraction data are available from many nanocrystals of dierent sizes lying in the same orientations without knowledge of the distribution of particle size or requiring atomic-resolution data. Triple correlation of the diraction patterns are made use of to reconiii
ContributorsWang, Xiaoyu (Author) / Spence, John C.H. (Thesis advisor) / Schmidt, Kevin (Committee member) / Doak, R. Bruce (Committee member) / Weierstall, Uwe (Committee member) / Ros, Robert (Committee member) / Arizona State University (Publisher)
Created2011
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., 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
Description
In disordered soft matter system, amorphous and crystalline components might be coexisted. The interaction between the two distinct structures and the correlation within the crystalline components are crucial to the macroscopic property of the such material. The spider dragline silk biopolymer, is one of such soft matter material that exhibits exceptional mechanical strength though its mass density is considerably small compare to structural metal. Through wide-angle X-ray scattering (WAXS), the research community learned that the silk fiber is mainly composed of amorphous backbone and $\beta$-sheet nano-crystals. However, the morphology of the crystalline system within the fiber is still not clear. Therefore, a combination of small-angle X-ray scattering experiments and stochastic simulation is designed here to reveal the nano-crystalline ordering in spider silk biopolymer. In addition, several density functional theory (DFT) calculations were performed to help understanding the interaction between amorphous backbone and the crystalline $\beta$-sheets.
By taking advantage of the prior information obtained from WAXS, a rather crude nano-crystalline model was initialized for further numerical reconstruction. Using Markov-Chain stochastic method, a hundreds of nanometer size $\beta$-sheet distribution model was reconstructed from experimental SAXS data, including silk fiber sampled from \textit{Latrodectus hesperus}, \textit{Nephila clavipes}, \textit{Argiope aurantia} and \textit{Araneus gemmoides}. The reconstruction method was implemented using MATLAB and C++ programming language and can be extended to study a broad range of disordered material systems.
By taking advantage of the prior information obtained from WAXS, a rather crude nano-crystalline model was initialized for further numerical reconstruction. Using Markov-Chain stochastic method, a hundreds of nanometer size $\beta$-sheet distribution model was reconstructed from experimental SAXS data, including silk fiber sampled from \textit{Latrodectus hesperus}, \textit{Nephila clavipes}, \textit{Argiope aurantia} and \textit{Araneus gemmoides}. The reconstruction method was implemented using MATLAB and C++ programming language and can be extended to study a broad range of disordered material systems.
ContributorsMou, Qiushi (Author) / Yarger, Jeffery (Thesis advisor) / Benmore, Chris (Committee member) / Holland, Gregory (Committee member) / Ros, Robert (Committee member) / Arizona State University (Publisher)
Created2015
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 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.
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