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- Creators: Barrett, The Honors College
- Creators: Beckstein, Oliver
Description
RNA granules are assemblies of RNA and proteins inside cells that serve multiple roles and functions. Some of the functions they serve in include a variety of organelles such as germ cell P granules, stress granules, and neuronal granules with diverse functions. Intrinsically disordered domains are abundant in the proteins responsible for RNA granules, and they have been attributed to the formation and degradation of RNA granules through a liquid-liquid phase separation (LLPS) process. LLPS is typically a reversible process where a homogenous fluid de- mixes into two distinct liquid phases. Here, 47 RNA granule proteins with such disordered regions have been surveyed. These proteins have been simulated using coarse-grained molecular simulations to determine size dependence on temperature change. Upper critical solution temperature (UCST) and lower critical solution temperature (LCST) are phase behaviors that can be calculated using the data gathered for scaling and phase behaviors of these proteins. We discovered that less charged amino acid contents are present in RNA granules in comparison to general disordered sequences. This is in line with the observation that charged amino acids are less preferred for the sequence to phase separate at physiological-relevant temperatures. More interestingly, there seems to be an even mix of sequences contributing to both UCST, LCST, and no phase behaviors and the average temperature dependent behaviors of all these proteins have a relatively weak temperature dependence within the temperature range 300 and 325K. The average suggest that these proteins might collectively contribute to RNA granules in a way that adapts to small temperature fluctuations.
ContributorsFrench, Nolan James (Author) / Zheng, Wenwei (Thesis director) / Garg, Vikas (Committee member) / College of Integrative Sciences and Arts (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Ionic liquids are salts with low melting temperatures that maintain their liquid form below 100 °C, or even at ambient temperature. Ionic liquids are conductive, electrochemically stable, non-volatile, and have a low vapor pressure, making them a class of excellent candidate materials for electrolytes in energy storage, electrodeposition, batteries, fuel cells, and supercapacitors. Due to their multiple advantages, the use of ionic liquids on Earth has been widely studied; however, further research must be done before their implementation in space. The extreme temperatures encountered during space travel and extra-terrestrial deployment have the potential to greatly affect the liquid electrolyte system. Examples of low temperature planetary bodies are the permanently shadowed sections of the moon or icy surfaces of Jupiter’s moons. Recent studies have explored the limits of glass transition temperatures for ionic liquid systems. The project is centered around the development of an ionic liquid system for a molecular electronic transducer seismometer that would be deployed on the low temperature system of Europa. For this project, molecular dynamics simulations used input intermolecular and intramolecular parameters that then simulated molecular interactions. Molecular dynamics simulations are based around the statistical mechanics of chemistry and help calculate equilibrium properties that are not easily calculated by hand. These simulations will give insight into what interactions are significant inside a ionic liquid solution. The simulations aim to create an understanding how ionic liquid electrolyte systems function at a molecular level. With this knowledge one can tune their system and its contents to adapt the systems properties to fit all environments the seismometers will experience.
ContributorsDavis, Vincent Champneys (Author) / Dai, Lenore (Thesis director) / Gliege, Marisa (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
In recent years, experimental and theoretical evidence has pointed to the existence of biologically active proteins that either include unstructured regions or are entirely unstructured. Referred to as intrinsically disordered proteins (IDPs), they are now known to be involved in diverse functions, much as any folded protein. Mutations in IDPs have been implicated in multiple neurodegenerative diseases. Considering the disordered nature of IDPs, there are limited structure features that can be used to quantify the disordered state. One such pair of variables are the radius of gyration (Rg) and the corresponding Flory’s scaling exponent, both of which characterize the dimension and size of the protein. It is generally understood that the sequence of an IDP affects its Rg and scaling exponent. Properties such as amino acid hydrophobicity and charge can play important roles in determining the Rg of an IDP, much as they affect the structure of a folded protein. However, it is nontrivial to directly predict Rg and scaling exponent from an IDP sequence. In this thesis, a coarse-grained model is used to simulate the Rg and scaling exponents of 10,000 randomly generated sequences mimicking the amino acid propensities of a typical IDP sequence. Such a database is then fed into an artificial neural network model to directly predict the scaling exponent from the sequence. The framework has not only made accurate and precise predictions (<1% error) in comparing to the simulation-obtained scaling exponent, but also suggest important sequence descriptors for such prediction. In addition, through varying the number of sequences for training the model, we suggest a minimum dataset of 100 sequences might be sufficient to achieve a 5% error of prediction, shedding light upon possible predictive models with only experimental inputs.
ContributorsBrown, Matthew D (Author) / Zheng, Wenwei (Thesis director) / Huffman, Holly (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Titanium dioxide is an essential material under research for energy and environmental applications, chiefly through its photocatalytic properties. These properties allow it to be used for water-splitting, detoxification, and photovoltaics, in addition to its conventional uses in pigmentation and sunscreen. Titanium dioxide exists in several polymorphic structures, of which the most common are rutile and anatase. We focused on anatase for the purposes of this research, due to its promising results for hydrolysis.
Anatase exists often in its reduced form (TiO2-x), enabling it to perform redox reactions through the absorption and release of oxygen into/from the crystal lattice. These processes result in structural changes, induced by defects in the material, which can theoretically be observed using advanced characterization methods. In situ electron microscopy is one of such methods, and can provide a window into these structural changes. However, in order to interpret the structural evolution caused by defects in materials, it is often necessary and pertinent to use atomistic simulations to compare the experimental images with models.
In this thesis project, we modeled the defect structures in anatase, around oxygen vacancies and at surfaces, using molecular dynamics, benchmarked with density functional theory. Using a “reactive” forcefield designed for the simulation of interactions between anatase and water that can model and treat bonding through the use of bond orders, different vacancy structures were analyzed and simulated. To compare these theoretical, generated models with experimental data, the “multislice approach” to TEM image simulation was used. We investigated a series of different vacancy configurations and surfaces and generated fingerprints for comparison with TEM experiments. This comparison demonstrated a proof of concept for a technique suggesting the possibility for the identification of oxygen vacancy structures directly from TEM images. This research aims to improve our atomic-level understanding of oxide materials, by providing a methodology for the analysis of vacancy formation from very subtle phenomena in TEM images.
Anatase exists often in its reduced form (TiO2-x), enabling it to perform redox reactions through the absorption and release of oxygen into/from the crystal lattice. These processes result in structural changes, induced by defects in the material, which can theoretically be observed using advanced characterization methods. In situ electron microscopy is one of such methods, and can provide a window into these structural changes. However, in order to interpret the structural evolution caused by defects in materials, it is often necessary and pertinent to use atomistic simulations to compare the experimental images with models.
In this thesis project, we modeled the defect structures in anatase, around oxygen vacancies and at surfaces, using molecular dynamics, benchmarked with density functional theory. Using a “reactive” forcefield designed for the simulation of interactions between anatase and water that can model and treat bonding through the use of bond orders, different vacancy structures were analyzed and simulated. To compare these theoretical, generated models with experimental data, the “multislice approach” to TEM image simulation was used. We investigated a series of different vacancy configurations and surfaces and generated fingerprints for comparison with TEM experiments. This comparison demonstrated a proof of concept for a technique suggesting the possibility for the identification of oxygen vacancy structures directly from TEM images. This research aims to improve our atomic-level understanding of oxide materials, by providing a methodology for the analysis of vacancy formation from very subtle phenomena in TEM images.
ContributorsShindel, Benjamin Noam (Author) / Crozier, Peter (Thesis director) / Anwar, Shahriar (Committee member) / Singh, Arunima (Committee member) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Transition metal ions such as Zn2+, Mn2+, Co2+, and Fe2+ play crucial roles in organisms from all kingdoms of life. The homeostasis of these ions is mainly regulated by a group of secondary transporters from the cation diffusion facilitator (CDF) family. The mammalian zinc transporters (ZnTs), a subfamily of CDF, have been an important target for study as they are associated with several diseases, such as diabetes, delayed growth and osteopenia, Alzheimer’s disease, and Parkinsonism. The bacterial homolog of ZnTs, YiiP, is the first CDF transporter with a determined structure and is used as a model for studying the structural and mechanistic properties of CDF transporters. On the other hand, Molecular dynamics simulation has emerged as a valuable computational tool for exploring the physical basis of biological macromolecules' structure and function with atomic precision at femtosecond resolution. This work aims to elucidate the roles of the three Zn$2+ binding sites found on each YiiP protomer and the role of protons in the transport process of CDFs, which remain under debate despite previous thermodynamic and structural studies on YiiP. Cryo-EM, microscale thermophoresis (MST) and molecular dynamics (MD) simulations were used to address these questions. With a Zn2+ model that accurately reproduces experimental structures of the binding clusters, the dynamical influence of zinc binding on the transporter was accessed through MD simulations, which was consistent with the new cryo-EM structures. Zinc binding affinities obtained through MST were used to infer the stoichiometry of Zn2+/H+ antiport in combination with a microscopic thermodynamic model and constant pH simulations. The most likely microstates of H$^+$ and Zn2+ binding indicated a transport stoichiometry of 1 Zn2+ to 2-3 H+ depending on the external pH. A model describing the entire transport cycle of YiiP was finally built on these findings, providing insight into the structural and mechanistic properties of CDF transporters.
ContributorsFan, Shujie (Author) / Beckstein, Oliver (Thesis advisor) / Ozkan, Banu (Committee member) / Heyden, Matthias (Committee member) / Van Horn, Wade (Committee member) / Arizona State University (Publisher)
Created2023
Description
Natures hardworking machines, proteins, are dynamic beings. Comprehending the role of dynamics in mediating allosteric effects is paramount to unraveling the intricate mechanisms underlying protein function and devising effective protein design strategies. Thus, the essential objective of this thesis is to elucidate ways to use protein dynamics based tools integrated with evolution and docking techniques to investigate the effect of distal allosteric mutations on protein function and further rationally design proteins. To this end, I first employed molecular dynamics (MD) simulations, Dynamic Flexibility Index (DFI) and Dynamic Coupling Index (DCI) on PICK1 PDZ, Butyrylcholinesterase (BChE), and Dihydrofolate reductase (DHFR) to uncover how these proteins utilize allostery to tune activity. Moreover, a new classification technique (“Controller”/“Controlled”) based on asymmetry in dynamic coupling is developed and applied to DHFR to elucidate the effect of allosteric mutations on enzyme activity. Subsequently, an MD driven dynamics design approach is applied on TEM-1 β-lactamase to tailor its activity against β-lactam antibiotics. New variants were created, and using a novel analytical approach called "dynamic distance analysis" (DDA) the degree of dynamic similarity between these variants were quantified. The experimentally confirmed results of these studies showed that the implementation of MD driven dynamics design holds significant potential for generating variants that can effectively modulate activity and stability. Finally, I introduced an evolutionary guided molecular dynamics driven protein design approach, integrated co-evolution and dynamic coupling (ICDC), to identify distal residues that modulate binding site dynamics through allosteric mechanisms. After validating the accuracy of ICDC with a complete mutational data set of β-lactamase, I applied it to Cyanovirin-N (CV-N) to identify allosteric positions and mutations that can modulate binding affinity. To further investigate the impact of mutations on the identified allosteric sites, I subjected putative mutants to binding analysis using Adaptive BP-Dock. Experimental validation of the computational predictions demonstrated the efficacy of integrating MD, DFI, DCI, and evolution to guide protein design. Ultimately, the research presented in this thesis demonstrates the effectiveness of using evolutionary guided molecular dynamics driven design alongside protein dynamics based tools to examine the significance of allosteric interactions and their influence on protein function.
ContributorsKazan, Ismail Can (Author) / Ozkan, Sefika Banu (Thesis advisor) / Ghirlanda, Giovanna (Thesis advisor) / Mills, Jeremy (Committee member) / Beckstein, Oliver (Committee member) / Arizona State University (Publisher)
Created2023
Description
Na+/H+ antiporters are vital membrane proteins for cell homeostasis, transporting Na+ ions in exchange for H+ across the lipid bilayer. In humans, dysfunction of these transporters are implicated in hypertension, heart failure, epilepsy, and autism, making them well-established drug targets. Although experimental structures for bacterial homologs of the human Na+/H+ have been obtained, the detailed mechanism for ion transport is still not well-understood. The most well-studied of these transporters, Escherichia coli NhaA, known to transport 2 H+ for every Na+ extruded, was recently shown to bind H+ and Na+ at the same binding site, for which the two ion species compete. Using molecular dynamics simulations, the work presented in this dissertation shows that Na+ binding disrupts a previously-unidentified salt bridge between two conserved residues, suggesting that one of these residues, Lys300, may participate directly in transport of H+. This work also demonstrates that the conformational change required for ion translocation in a homolog of NhaA, Thermus thermophilus NapA, thought by some to involve only small helical movements at the ion binding site, is a large-scale, rigid-body movement of the core domain relative to the dimerization domain. This elevator-like transport mechanism translates a bound Na+ up to 10 Å across the membrane. These findings constitute a major shift in the prevailing thought on the mechanism of these transporters, and serve as an exciting launchpad for new developments toward understanding that mechanism in detail.
ContributorsDotson, David L (Author) / Beckstein, Oliver (Thesis advisor) / Ozkan, Sefika B (Committee member) / Ros, Robert (Committee member) / Van Horn, Wade (Committee member) / Arizona State University (Publisher)
Created2016
Description
In a typical living cell, millions to billions of proteins—nanomachines that fluctuate and cycle among many conformational states—convert available free energy into mechanochemical work. A fundamental goal of biophysics is to ascertain how 3D protein structures encode specific functions, such as catalyzing chemical reactions or transporting nutrients into a cell. Protein dynamics span femtosecond timescales (i.e., covalent bond oscillations) to large conformational transition timescales in, and beyond, the millisecond regime (e.g., glucose transport across a phospholipid bilayer). Actual transition events are fast but rare, occurring orders of magnitude faster than typical metastable equilibrium waiting times. Equilibrium molecular dynamics (EqMD) can capture atomistic detail and solute-solvent interactions, but even microseconds of sampling attainable nowadays still falls orders of magnitude short of transition timescales, especially for large systems, rendering observations of such "rare events" difficult or effectively impossible.
Advanced path-sampling methods exploit reduced physical models or biasing to produce plausible transitions while balancing accuracy and efficiency, but quantifying their accuracy relative to other numerical and experimental data has been challenging. Indeed, new horizons in elucidating protein function necessitate that present methodologies be revised to more seamlessly and quantitatively integrate a spectrum of methods, both numerical and experimental. In this dissertation, experimental and computational methods are put into perspective using the enzyme adenylate kinase (AdK) as an illustrative example. We introduce Path Similarity Analysis (PSA)—an integrative computational framework developed to quantify transition path similarity. PSA not only reliably distinguished AdK transitions by the originating method, but also traced pathway differences between two methods back to charge-charge interactions (neglected by the stereochemical model, but not the all-atom force field) in several conserved salt bridges. Cryo-electron microscopy maps of the transporter Bor1p are directly incorporated into EqMD simulations using MD flexible fitting to produce viable structural models and infer a plausible transport mechanism. Conforming to the theme of integration, a short compendium of an exploratory project—developing a hybrid atomistic-continuum method—is presented, including initial results and a novel fluctuating hydrodynamics model and corresponding numerical code.
Advanced path-sampling methods exploit reduced physical models or biasing to produce plausible transitions while balancing accuracy and efficiency, but quantifying their accuracy relative to other numerical and experimental data has been challenging. Indeed, new horizons in elucidating protein function necessitate that present methodologies be revised to more seamlessly and quantitatively integrate a spectrum of methods, both numerical and experimental. In this dissertation, experimental and computational methods are put into perspective using the enzyme adenylate kinase (AdK) as an illustrative example. We introduce Path Similarity Analysis (PSA)—an integrative computational framework developed to quantify transition path similarity. PSA not only reliably distinguished AdK transitions by the originating method, but also traced pathway differences between two methods back to charge-charge interactions (neglected by the stereochemical model, but not the all-atom force field) in several conserved salt bridges. Cryo-electron microscopy maps of the transporter Bor1p are directly incorporated into EqMD simulations using MD flexible fitting to produce viable structural models and infer a plausible transport mechanism. Conforming to the theme of integration, a short compendium of an exploratory project—developing a hybrid atomistic-continuum method—is presented, including initial results and a novel fluctuating hydrodynamics model and corresponding numerical code.
ContributorsSeyler, Sean L (Author) / Beckstein, Oliver (Thesis advisor) / Chamberlin, Ralph (Committee member) / Matyushov, Dmitry (Committee member) / Thorpe, Michael F (Committee member) / Vaiana, Sara (Committee member) / Arizona State University (Publisher)
Created2017
Description
In order to better understand the physical properties of polyethylene, an extremely common plastic used mostly in packaging, many scientists and engineers use olecular dynamics. To reduce the computational expense associated with traditional atomistic molecular dynamics, coarse-grained molecular dynamics is often used. Coarse-grained molecular dynamics groups multiple atoms into single beads, reducing the number of degrees of freedom in a system and eliminating smaller atoms with faster kinematics. However, even coarse-grained methods have their limitations, one of which is timestep duration, which is limited by the maximum vibrational frequency in the coarse-grained system. To study this limitation, a coarse-grained model of polyethylene was created such that every C 2 H 4 unit was replaced with a bead. Coarse-grained potentials for bond-stretching, bond-bending, and non-bonded interaction were generated using the iterative Boltzmann inversion method, which matches coarse-grained distribution functions to atomistic distribution functions. After the creation of the model, the coarse-grained potentials were rescaled by a constant so that they were less stiff, decreasing the maximum vibrational frequency of the system. It is found that by diminishing the bond-stretching potential to 6.25% of its original value, the maximum stable timestep can be increased 85% over that of the unmodified potential functions. The results of this work suggest that it may be possible to simulate lengthy processes, such as the crystallization of polyethylene, in less time with adjusted coarse-grained potentials. Additionally, the large discrepancies in the speed of bond-stretching, bond-bending, and non- bonded interaction dynamics suggest that a multi-timestep method may be worth investigating in future work.
ContributorsWiles, Christian Scott (Author) / Oswald, Jay (Thesis director) / Dai, Lenore (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12