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- Creators: Arizona State University
- Creators: Barrett, The Honors College
- Creators: Beckstein, Oliver
Description
Molecular dynamics (MD) simulations provide a particularly useful approach to understanding conformational change in biomolecular systems. MD simulations provide an atomistic, physics-based description of the motions accessible to biomolecular systems on the pico- to micro-second timescale, yielding important insight into the free energy of the system, the dynamical stability of contacts and the role of correlated motions in directing the motions of the system. In this thesis, I use molecular dynamics simulations to provide molecular mechanisms that rationalize structural, thermodynamic, and mutation data on the interactions between the lac repressor headpiece and its O1 operator DNA as well as the ERK2 protein kinase. I performed molecular dynamics simulations of the lac repressor headpiece - O1 operator complex at the natural angle as well as at under- and overbent angles to assess the factors that determine the natural DNA bending angle. I find both energetic and entropic factors contribute to recognition of the natural angle. At the natural angle the energy of the system is minimized by optimization of protein-DNA contacts and the entropy of the system is maximized by release of water from the protein-DNA interface and decorrelation of protein motions. To identify the mechanism by which mutations lead to auto-activation of ERK2, I performed a series of molecular dynamics simulations of ERK1/2 in various stages of activation as well as the constitutively active Q103A, I84A, L73P and R65S ERK2 mutants. My simulations indicate the importance of domain closure for auto-activation and activity regulation. My results enable me to predict two loss-of-function mutants of ERK2, G83A and Q64C, that have been confirmed in experiments by collaborators. One of the powerful capabilities of MD simulations in biochemistry is the ability to find low free energy pathways that connect and explain disparate structural data on biomolecular systems. An extention of the targeted molecular dynamics technique using constraints on internal coordinates will be presented and evaluated. The method gives good results for the alanine dipeptide, but breaks down when applied to study conformational changes in GroEL and adenylate kinase.
ContributorsBarr, Daniel Alan (Author) / van der Vaart, Arjan (Thesis advisor) / Matyushov, Dmitry (Committee member) / Wolf, George (Committee member) / Shumway, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
Liquid-liquid interfaces serve as ideal 2-D templates on which solid particles can self-assemble into various structures. These self-assembly processes are important in fabrication of micron-sized devices and emulsion formulation. At oil/water interfaces, these structures can range from close-packed aggregates to ordered lattices. By incorporating an ionic liquid (IL) at the interface, new self-assembly phenomena emerge. ILs are ionic compounds that are liquid at room temperature (essentially molten salts at ambient conditions) that have remarkable properties such as negligible volatility and high chemical stability and can be optimized for nearly any application. The nature of IL-fluid interfaces has not yet been studied in depth. Consequently, the corresponding self-assembly phenomena have not yet been explored. We demonstrate how the unique molecular nature of ILs allows for new self-assembly phenomena to take place at their interfaces. These phenomena include droplet bridging (the self-assembly of both particles and emulsion droplets), spontaneous particle transport through the liquid-liquid interface, and various gelation behaviors. In droplet bridging, self-assembled monolayers of particles effectively "glue" emulsion droplets to one another, allowing the droplets to self-assembly into large networks. With particle transport, it is experimentally demonstrated the ILs overcome the strong adhesive nature of the liquid-liquid interface and extract solid particles from the bulk phase without the aid of external forces. These phenomena are quantified and corresponding mechanisms are proposed. The experimental investigations are supported by molecular dynamics (MD) simulations, which allow for a molecular view of the self-assembly process. In particular, we show that particle self-assembly depends primarily on the surface chemistry of the particles and the non-IL fluid at the interface. Free energy calculations show that the attractive forces between nanoparticles and the liquid-liquid interface are unusually long-ranged, due to capillary waves. Furthermore, IL cations can exhibit molecular ordering at the IL-oil interface, resulting in a slight residual charge at this interface. We also explore the transient IL-IL interface, revealing molecular interactions responsible for the unusually slow mixing dynamics between two ILs. This dissertation, therefore, contributes to both experimental and theoretical understanding of particle self-assembly at IL based interfaces.
ContributorsFrost, Denzil (Author) / Dai, Lenore L (Thesis advisor) / Torres, César I (Committee member) / Nielsen, David R (Committee member) / Squires, Kyle D (Committee member) / Rege, Kaushal (Committee member) / Arizona State University (Publisher)
Created2013
Description
Recently, the use of zinc oxide (ZnO) nanowires as an interphase in composite materials has been demonstrated to increase the interfacial shear strength between carbon fiber and an epoxy matrix. In this research work, the strong adhesion between ZnO and carbon fiber is investigated to elucidate the interactions at the interface that result in high interfacial strength. First, molecular dynamics (MD) simulations are performed to calculate the adhesive energy between bare carbon and ZnO. Since the carbon fiber surface has oxygen functional groups, these were modeled and MD simulations showed the preference of ketones to strongly interact with ZnO, however, this was not observed in the case of hydroxyls and carboxylic acid. It was also found that the ketone molecules ability to change orientation facilitated the interactions with the ZnO surface. Experimentally, the atomic force microscope (AFM) was used to measure the adhesive energy between ZnO and carbon through a liftoff test by employing highly oriented pyrolytic graphite (HOPG) substrate and a ZnO covered AFM tip. Oxygen functionalization of the HOPG surface shows the increase of adhesive energy. Additionally, the surface of ZnO was modified to hold a negative charge, which demonstrated an increase in the adhesive energy. This increase in adhesion resulted from increased induction forces given the relatively high polarizability of HOPG and the preservation of the charge on ZnO surface. It was found that the additional negative charge can be preserved on the ZnO surface because there is an energy barrier since carbon and ZnO form a Schottky contact. Other materials with the same ionic properties of ZnO but with higher polarizability also demonstrated good adhesion to carbon. This result substantiates that their induced interaction can be facilitated not only by the polarizability of carbon but by any of the materials at the interface. The versatility to modify the magnitude of the induced interaction between carbon and an ionic material provides a new route to create interfaces with controlled interfacial strength.
ContributorsGalan Vera, Magdian Ulises (Author) / Sodano, Henry A (Thesis advisor) / Jiang, Hanqing (Committee member) / Solanki, Kiran (Committee member) / Oswald, Jay (Committee member) / Speyer, Gil (Committee member) / Arizona State University (Publisher)
Created2013
Description
The goal of this theoretical study of infrared spectra was to ascertain to what degree molecules may be identified from their IR spectra and which spectral regions are best suited for this purpose. The frequencies considered range from the lowest frequency molecular vibrations in the far-IR, terahertz region (below ~3 THz or 100 cm-1) up to the highest frequency vibrations (~120 THz or 4000 cm-1). An emphasis was placed on the IR spectra of chemical and biological threat molecules in the interest of detection and prevention. To calculate IR spectra, the technique of normal mode analysis was applied to organic molecules ranging in size from 8 to 11,352 atoms. The IR intensities of the vibrational modes were calculated in terms of the derivative of the molecular dipole moment with respect to each normal coordinate. Three sets of molecules were studied: the organophosphorus G- and V-type nerve agents and chemically related simulants (15 molecules ranging in size from 11 to 40 atoms); 21 other small molecules ranging in size from 8 to 24 atoms; and 13 proteins ranging in size from 304 to 11,352 atoms. Spectra for the first two sets of molecules were calculated using quantum chemistry software, the last two sets using force fields. The "middle" set used both methods, allowing for comparison between them and with experimental spectra from the NIST/EPA Gas-Phase Infrared Library. The calculated spectra of proteins, for which only force field calculations are practical, reproduced the experimentally observed amide I and II bands, but they were shifted by approximately +40 cm-1 relative to experiment. Considering the entire spectrum of protein vibrations, the most promising frequency range for differentiating between proteins was approximately 600-1300 cm-1 where water has low absorption and the proteins show some differences.
ContributorsMott, Adam J (Author) / Rez, Peter (Thesis advisor) / Ozkan, Banu (Committee member) / Shumway, John (Committee member) / Thorpe, Michael (Committee member) / Vaiana, Sara (Committee member) / Arizona State University (Publisher)
Created2012
Description
The rheological properties at liquid-liquid interfaces are important in many industrial processes such as manufacturing foods, pharmaceuticals, cosmetics, and petroleum products. This dissertation focuses on the study of linear viscoelastic properties at liquid-liquid interfaces by tracking the thermal motion of particles confined at the interfaces. The technique of interfacial microrheology is first developed using one- and two-particle tracking, respectively. In one-particle interfacial microrheology, the rheological response at the interface is measured from the motion of individual particles. One-particle interfacial microrheology at polydimethylsiloxane (PDMS) oil-water interfaces depends strongly on the surface chemistry of different tracer particles. In contrast, by tracking the correlated motion of particle pairs, two-particle interfacial microrheology significantly minimizes the effects from tracer particle surface chemistry and particle size. Two-particle interfacial microrheology is further applied to study the linear viscoelastic properties of immiscible polymer-polymer interfaces. The interfacial loss and storage moduli at PDMS-polyethylene glycol (PEG) interfaces are measured over a wide frequency range. The zero-shear interfacial viscosity, estimated from the Cross model, falls between the bulk viscosities of two individual polymers. Surprisingly, the interfacial relaxation time is observed to be an order of magnitude larger than that of the PDMS bulk polymers. To explore the fundamental basis of interfacial nanorheology, molecular dynamics (MD) simulations are employed to investigate the nanoparticle dynamics. The diffusion of single nanoparticles in pure water and low-viscosity PDMS oils is reasonably consistent with the prediction by the Stokes-Einstein equation. To demonstrate the potential of nanorheology based on the motion of nanoparticles, the shear moduli and viscosities of the bulk phases and interfaces are calculated from single-nanoparticle tracking. Finally, the competitive influences of nanoparticles and surfactants on other interfacial properties, such as interfacial thickness and interfacial tension are also studied by MD simulations.
ContributorsSong, Yanmei (Author) / Dai, Lenore L (Thesis advisor) / Jiang, Hanqing (Committee member) / Lin, Jerry Y S (Committee member) / Raupp, Gregory B (Committee member) / Sierks, Michael R (Committee member) / Arizona State University (Publisher)
Created2011
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
Molecular Dynamics (MD) simulations are ubiquitous throughout the physical sci-ences; they are critical in understanding how particle structures evolve over time
given a particular energy function. A software package called ParSplice introduced a
new method to generate these simulations in parallel that has significantly inflated
their length. Typically, simulations are short discrete Markov chains, only captur-
ing a few microseconds of a particle’s behavior and containing tens of thousands of
transitions between states; in contrast, a typical ParSplice simulation can be as long
as a few milliseconds, containing tens of millions of transitions. Naturally, sifting
through data of this size is impossible by hand, and there are a number of visualiza-
tion systems that provide comprehensive and intuitive analyses of particle structures
throughout MD simulations. However, no visual analytics systems have been built
that can manage the simulations that ParSplice produces. To analyze these large
data-sets, I built a visual analytics system that provides multiple coordinated views
that simultaneously describe the data temporally, within its structural context, and
based on its properties. The system provides fluid and powerful user interactions
regardless of the size of the data, allowing the user to drill down into the data-set to
get detailed insights, as well as run and save various calculations, most notably the
Nudged Elastic Band method. The system also allows the comparison of multiple
trajectories, revealing more information about the general behavior of particles at different temperatures, energy states etc.
ContributorsHnatyshyn, Rostyslav (Author) / Maciejewski, Ross (Thesis advisor) / Bryan, Chris (Committee member) / Ahrens, James (Committee member) / Arizona State University (Publisher)
Created2022