1000 resultados para Leucine Dynamics
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Thesis (Ph.D.)--University of Washington, 2016-05
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Acetohydroxy acid isomeroreductase is a key enzyme involved in the biosynthetic pathway of the amino acids isoleucine, valine, and leucine. This enzyme is of great interest in agrochemical research because it is present only in plants and microorganisms, making it a potential target for specific herbicides and fungicides. Moreover, it catalyzes an unusual two-step reaction that is of great fundamental interest. With a view to characterizing both the mechanism of inhibition by potential herbicides and the complex reaction mechanism, various techniques of enzymology, molecular biology, mass spectrometry, X-ray crystallography, and theoretical simulation have been used. The results and conclusions of these studies are described briefly in this paper.
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As part of the PeECE II mesocosm project, we investigated the effects of pCO2 levels on the initial step of heterotrophic carbon cycling in the surface ocean. The activities of microbial extracellular enzymes hydrolyzing 4 polysaccharides were measured during the development of a natural phytoplankton bloom under pCO2 conditions representing glacial (190 µatm) and future (750 µatm) atmospheric pCO2. We observed that (1) chondroitin hydrolysis was variable throughout the pre-, early- and late-bloom phases, (2) fucoidanase activity was measurable only in the glacial mesocosm as the bloom developed, (3) laminarinase activity was low and constant, and (4) xylanase activity declined as the bloom progressed. Concurrent measurements of microbial community composition, using denaturing-gradient gel electrophoresis (DGGE), showed that the 2 mesocosms diverged temporally, and from one another, especially in the late-bloom phase. Enzyme activities correlated with bloom phase and pCO2, suggesting functional as well as compositional changes in microbial communities in the different pCO2 environments. These changes, however, may be a response to temporal changes in the development of phytoplankton communities that differed with the pCO2 environment. We hypothesize that the phytoplankton communities produced dissolved organic carbon (DOC) differing in composition, a hypothesis supported by changing amino acid composition of the DOC, and that enzyme activities responded to changes in substrates. Enzyme activities observed under different pCO2 conditions likely reflect both genetic and population-level responses to changes occurring among multiple components of the microbial loop.
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A mesocosm experiment was conducted to investigate the impact of rising fCO2 on the build-up and decline of organic matter during coastal phytoplankton blooms. Five mesocosms (~38 m³ each) were deployed in the Baltic Sea during spring (2009) and enriched with CO2 to yield a gradient of 355-862 µatm. Mesocosms were nutrient fertilized initially to induce phytoplankton bloom development. Changes in particulate and dissolved organic matter concentrations, including dissolved high-molecular weight (>1 kDa) combined carbohydrates, dissolved free and combined amino acids as well as transparent exopolymer particles (TEP), were monitored over 21 days together with bacterial abundance, and hydrolytic extracellular enzyme activities. Overall, organic matter followed well-known bloom dynamics in all CO2 treatments alike. At high fCO2, higher dPOC:dPON during bloom rise, and higher TEP concentrations during bloom peak, suggested preferential accumulation of carbon-rich components. TEP concentration at bloom peak was significantly related to subsequent sedimentation of particulate organic matter. Bacterial abundance increased during the bloom and was highest at high fCO2. We conclude that increasing fCO2 supports production and exudation of carbon-rich components, enhancing particle aggregation and settling, but also providing substrate and attachment sites for bacteria. More labile organic carbon and higher bacterial abundance can increase rates of oxygen consumption and may intensify the already high risk of oxygen depletion in coastal seas in the future.
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Synthesis of a 33-residue, capped leucine zipper analogous to that in GCN4 is reported. Histidine and arginine residues are mutated to lysine to reduce the unfolding temperature. CD and ultracentrifugation studies indicate that the molecule is a two-stranded coiled coil under benign conditions. Versions of the same peptide are made with 99% 13Calpha at selected sites. One-dimensional 13C NMR spectra are assigned by inspection and used to study thermal unfolding equilibria over the entire transition from 8 to 73 degrees C. Spectra at the temperature extremes establish the approximate chemical shifts for folded and unfolded forms at each labeled site. Resonances for each amino acid appear at both locations at intermediate T, indicating that folded and unfolded forms interconvert slowly (> >2 ms) on the NMR time scale. Moreover, near room temperature, the structured form's resonance is double at several, but not all, sites, indicating at least two slowly interconverting, structured, local conformational substates. Analysis of the dynamics is possible. For example, near room temperature at the Val-9, Ala-24, and Gly-31 positions, the equilibrium constant for interconversion of the two structured forms is near unity and the time scale is > or= 10-20 ms.
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A recently developed spectral method for identifying metastable states in Markov chains is used to analyse the conformational dynamics of a four residue peptide Valine-Proline-Alanine-Leucine. We compare our results to empirically defined conformational states and show that the found metastable states correctly reproduce the conformational dynamics of the system.
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The dynamics of peptides and proteins generated by classical molecular dynamics (MD) is described by using a Markov model. The model is built by clustering the trajectory into conformational states and estimating transition probabilities between the states. Assuming that it is possible to influence the dynamics of the system by varying simulation parameters, we show how to use the Markov model to determine the parameter values that preserve the folded state of the protein and at the same time, reduce the folding time in the simulation. We investigate this by applying the method to two systems. The first system is an imaginary peptide described by given transition probabilities with a total folding time of 1 micros. We find that only small changes in the transition probabilities are needed to accelerate (or decelerate) the folding. This implies that folding times for slowly folding peptides and proteins calculated using MD cannot be meaningfully compared to experimental results. The second system is a four residue peptide valine-proline-alanine-leucine in water. We control the dynamics of the transitions by varying the temperature and the atom masses. The simulation results show that it is possible to find the combinations of parameter values that accelerate the dynamics and at the same time preserve the native state of the peptide. A method for accelerating larger systems without performing simulations for the whole folding process is outlined.
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We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500 ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100 ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.
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Conformational transitions in proteins define their biological activity and can be investigated in detail using the Markov state model. The fundamental assumption on the transitions between the states, their Markov property, is critical in this framework. We test this assumption by analyzing the transitions obtained directly from the dynamics of a molecular dynamics simulated peptide valine-proline-alanine-leucine and states defined phenomenologically using clustering in dihedral space. We find that the transitions are Markovian at the time scale of ˜ 50 ps and longer. However, at the time scale of 30–40 ps the dynamics loses its Markov property. Our methodology reveals the mechanism that leads to non-Markov behavior. It also provides a way of regrouping the conformations into new states that now possess the required Markov property of their dynamics.
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As graphene has become one of the most important materials, there is renewed interest in other similar structures. One example is silicene, the silicon analogue of graphene. It shares some of the remarkable graphene properties, such as the Dirac cone, but presents some distinct ones, such as a pronounced structural buckling. We have investigated, through density functional based tight-binding (DFTB), as well as reactive molecular dynamics (using ReaxFF), the mechanical properties of suspended single-layer silicene. We calculated the elastic constants, analyzed the fracture patterns and edge reconstructions. We also addressed the stress distributions, unbuckling mechanisms and the fracture dependence on the temperature. We analysed the differences due to distinct edge morphologies, namely zigzag and armchair.
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The role of orbital differentiation on the emergence of superconductivity in the Fe-based superconductors remains an open question to the scientific community. In this investigation, we employ a suitable microscopic spin probe technique, namely Electron Spin Resonance (ESR), to investigate this issue on selected chemically substituted BaFe2As2 single crystals. As the spin-density wave (SDW) phase is suppressed, we observe a clear increase of the Fe 3d bands anisotropy along with their localization at the FeAs plane. Such an increase of the planar orbital content is interestingly independent of the chemical substitution responsible for suppressing the SDW phase. As a consequence, the magnetic fluctuations in combination with this particular symmetry of the Fe 3d bands are propitious ingredients for the emergence of superconductivity in this class of materials.
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This study investigates the practices involved in the production of knowledge about menopause at Caism, Unicamp, a reference center for public policies for women's health. Gynecological appointments and psychological support meetings were observed, and women and doctors were interviewed in order to identify what discourse circulates there and how different actors are brought in to ensure that the knowledge produced attains credibility and travels beyond the boundaries of the teaching hospital to become universal. The analysis is based on localized studies aligned with social studies of science and technology.
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This study investigates the practices involved in the production of knowledge about menopause at Caism, Unicamp, a reference center for public policies for women's health. Gynecological appointments and psychological support meetings were observed, and women and doctors were interviewed in order to identify what discourse circulates there and how different actors are brought in to ensure that the knowledge produced attains credibility and travels beyond the boundaries of the teaching hospital to become universal. The analysis is based on localized studies aligned with social studies of science and technology.