1,720,984 research outputs found
The origin of pressure resistance in deep-sea lactate dehydrogenase
No full textHigh hydrostatic pressure has a dramatic effect on biochemical systems, as exposure to high pressure can result in structural perturbations ranging from dissociation of protein complexes to complete denaturation. The deep ocean presents an interesting paradox since it is teeming with life despite the high-pressure environment. This is due to evolutionary adaptations in deep-sea organisms, such as amino acid substitutions in their proteins, which aid in resisting the denaturing effects of pressure. However, the physico-chemical mechanism by which these substitutions can induce pressure resistance remains unknown. Here, we use molecular dynamics simulations to study pressure-adapted lactate dehydrogenase from the deep-sea abyssal grenadier (C. armatus), in comparison with that of the shallow-water Atlantic cod (G. morhua). Alchemical thermodynamic integration and the Archimedean Displacement Method were used to determine whether pressure resistance is due to a thermodynamic stabilization of the native state of the protein or to an increase in the volume of the denatured state. We report that the amino acid substitutions destabilize the folded protein, but pressure resistance is achieved through an increase in compressibility for the pressure-adapted protein. This dataset contains input files and run scripts for the alchemical free energy calculations and the volume calculations. See README.txt files within each archive for specific details on how to run and analyze the calculations
AutoDock Vina calculations of the µ-Opioid Receptor Complexed with Carfentanil Analogs
No full textAutoDock Vina 1.2.3 was used to calculate binding poses and binding energies for carfentanil and its structural analogs inside the binding site of the µ-opioid receptor. All structural analogues exhibited identical binding poses to carfentanil with similar binding energies, indicating that the analogs may be biologically active. This dataset contains AutoDock Vina input files, final docked structures and binding energies, and instructions for running the calculations
DFT trajectory dataset for "Understanding high pressure molecular hydrogen with a hierarchical machine-learned potential"
No full textThe hydrogen phase diagram has several unusual features which are well reproduced by density functional calculations. Unfortunately, these calculations do not provide good physical insights into why those features occur. Here, we present a fast interatomic potential, which reproduces the molecular hydrogen phases: orientationally disordered Phase I; broken-symmetry Phase II, efficiently-packed Phase III and reentrant melt curve. The H2 vibrational frequency drops at high pressure because of increased coupling between neighbouring molecules, not bond weakening. Liquid H2 is denser than coexisting close-packed solid at high pressure because the favored molecular orientation switches from quadrupole-energy-minimizing to steric-repulsion-minimizing. The latter allows molecules to get closer together, without the atoms getting closer, but cannot be achieved within in a close-packed layer due to frustration. A similar effect causes negative thermal expansion. At high pressure, rotation is hindered in Phase I, such that it cannot be regarded as a molecular rotor phase.
This dataset contains DFT trajectory data used for fitting the machine learned interatomic potential
Input files and data for "Phase behaviour of the quantum Lennard-Jones solid"
No full textThe Lennard-Jones potential is perhaps one of the most widely-used models for the interaction of uncharged particles, such as noble gas solids. The phase diagram of the classical LJ solid is known to exhibit transitions between hcp and fcc phases. However, the phase behaviour of the quantum Lennard Jones solid remains unknown. Thermodynamic integration based on path integral molecular dynamics and lattice dynamics calculations are used to study the phase stability of the hcp and fcc Lennard Jones solids. The hcp phase is shown to be stabilized by quantum effects in PIMD while fcc is shown to be favoured by lattice dynamics, which suggests a possible re-entrant low pressure hcp phase for highly quantum systems. Implications for the phase stability of noble gas solids are discussed. For parameters equating to Helium, the expansion due to zero-point vibrations is associated with quantum melting: neither crystal structure is stable at zero pressure.
This dataset contains input files and run scripts for the quasiharmonic calculations using GULP, and the PIMD calculations using i-PI and LAMMPS. See README.txt files within each archive for specific details on how to run and analyze the calculations
Isotope quantum effects in the metallization transition in liquid hydrogen
No full textQuantum effects in condensed matter normally only occur at low temperatures. Here we show a large quantum effect in high-pressure liquid hydrogen at thousands of Kelvins. We show that the metallization transition in hydrogen is subject to a very large isotope effect, occurring hundreds of degrees lower than the equivalent transition in deuterium. We examined this using path integral molecular dynamics simulations which identify a liquid-liquid transition involving atomization, metallization, and changes in viscosity, specific heat and compressibility. The difference between H2 and D2 is a quantum mechanical effect which can be associated with the larger zero-point energy in H2 weakening the covalent bond. Our results mean that experimental results on deuterium must be corrected before they are relevant to understanding hydrogen at planetary conditions.van de Bund, Sebastiaan; Ackland, Graeme J.; Wiebe, Heather. (2021). Isotope quantum effects in the metallization transition in liquid hydrogen, [dataset]. University of Edinburgh. School of Physics and Astronomy. https://doi.org/10.7488/ds/3042
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Understanding high pressure molecular hydrogen with a hierarchical machine-learned potential
No full textThe hydrogen phase diagram has several unusual features which are well reproduced by density functional calculations. Unfortunately, these calculations do not provide good physical insights into why those features occur. Here, we present a fast interatomic potential, which reproduces the molecular hydrogen phases: orientationally disordered Phase I; broken-symmetry Phase II, efficiently-packed Phase III and reentrant melt curve. The H2 vibrational frequency drops at high pressure because of increased coupling between neighbouring molecules, not bond weakening. Liquid H2 is denser than coexisting close-packed solid at high pressure because the favored molecular orientation switches from quadrupole-energy-minimizing to steric-repulsion-minimizing. The latter allows molecules to get closer together, without the atoms getting closer, but cannot be achieved within in a close-packed layer due to frustration. A similar effect causes negative thermal expansion. At high pressure, rotation is hindered in Phase I, such that it cannot be regarded as a molecular rotor phase. This dataset contains DFT trajectory data used for fitting the machine learned interatomic potential.Zong, Hongxiang; Wiebe, Heather; Ackland, Graeme J. (2020). Understanding high pressure molecular hydrogen with a hierarchical machine-learned potential, [dataset]. University of Edinburgh. School of Physics & Astronomy. https://doi.org/10.7488/ds/2874
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