The Experts below are selected from a list of 711261 Experts worldwide ranked by ideXlab platform
Michael Habeck - One of the best experts on this subject based on the ideXlab platform.
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Confidence-guided Local Structure prediction with HHfrag.
PloS one, 2013Co-Authors: Ivan Kalev, Michael HabeckAbstract:We present a method to assess the reliability of Local Structure prediction from sequence. We introduce a greedy algorithm for filtering and enrichment of dynamic fragment libraries, compiled with remote-homology detection methods such as HHfrag. After filtering false hits at each target position, we reduce the fragment library to a minimal set of representative fragments, which are guaranteed to have correct Local Structure in regions of detectable conservation. We demonstrate that the location of conserved motifs in a protein sequence can be predicted by examining the recurrence and structural homogeneity of detected fragments. The resulting confidence score correlates with the Local RMSD of the representative fragments and allows us to predict torsion angles from sequence with better accuracy compared to existing machine learning methods.
Matthias Wuttig - One of the best experts on this subject based on the ideXlab platform.
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unravelling the interplay of Local Structure and physical properties in phase change materials
Nature Materials, 2006Co-Authors: Wojciech Welnic, C. Steimer, Ariesto Pamungkas, Ralf Detemple, Stefan Blugel, Matthias WuttigAbstract:Unravelling the interplay of Local Structure and physical properties in phase-change materials
David J. Srolovitz - One of the best experts on this subject based on the ideXlab platform.
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topological framework for Local Structure analysis in condensed matter
Proceedings of the National Academy of Sciences of the United States of America, 2015Co-Authors: Emanuel A Lazar, Jian Han, David J. SrolovitzAbstract:Physical systems are frequently modeled as sets of points in space, each representing the position of an atom, molecule, or mesoscale particle. As many properties of such systems depend on the underlying ordering of their constituent particles, understanding that Structure is a primary objective of condensed matter research. Although perfect crystals are fully described by a set of translation and basis vectors, real-world materials are never perfect, as thermal vibrations and defects introduce significant deviation from ideal order. Meanwhile, liquids and glasses present yet more complexity. A complete understanding of Structure thus remains a central, open problem. Here we propose a unified mathematical framework, based on the topology of the Voronoi cell of a particle, for classifying Local Structure in ordered and disordered systems that is powerful and practical. We explain the underlying reason why this topological description of Local Structure is better suited for structural analysis than continuous descriptions. We demonstrate the connection of this approach to the behavior of physical systems and explore how crystalline Structure is compromised at elevated temperatures. We also illustrate potential applications to identifying defects in plastically deformed polycrystals at high temperatures, automating analysis of complex Structures, and characterizing general disordered systems.
Parbati Biswas - One of the best experts on this subject based on the ideXlab platform.
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Local Structure and Dynamics of Hydration Water in Intrinsically Disordered Proteins.
Journal of Physical Chemistry B, 2015Co-Authors: Pooja Rani, Parbati BiswasAbstract:Hydration water around protein surface plays a key role in Structure, folding and dynamics of proteins. Intrinsically disordered proteins lack secondary and/or tertiary Structure in their native state. Thus, characterizing the Local Structure and dynamics of hydration water around disordered proteins is challenging for both experimentalists and theoreticians. The Local Structure, orientation and dynamics of hydration water in the vicinity of intrinsically disordered proteins is investigated through molecular dynamics simulations. The analysis of the hydration capacity reveals that the disordered proteins have much larger binding capacity for hydration water than globular proteins. The surface and radial distribution of water molecules around the disordered proteins depict a similar trend. The Local Structure of the hydration water evaluated in terms of the tetrahedral order parameter, shows a higher order among the water molecules surrounding disordered proteins/regions. The residence time of water molecu...
A. R. Moodenbaugh - One of the best experts on this subject based on the ideXlab platform.
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Local Structure in the stripe phase of La1.6-xSrxNd0.4CuO4
Physical Review B, 2002Co-Authors: Sang-wook Han, Edward A. Stern, Daniel Haskel, A. R. MoodenbaughAbstract:We describe the Local Structure of crystalline La 1 . 6 - x Sr x Nd 0 . 4 CuO 4 (x = 0.12, 0.16) in the temperature range 10-300 K as determined from orientation-dependent La K-edge x-ray absorption fine Structure (XAFS) measurements. Such XAFS measurements of c-axis-aligned powders permit distinguishing like atoms at similar bonding distances because the measurement determines the angle of the bonds relative to the c axis. The Local Structure of x = 0.12 about La atoms up to their fourth nearest neighbors, the distance which can reliably be probed by XAFS, does not correspond to any of the average periodic Structures determined for this material by diffraction. The Cu-O 6 octahedra for x = 0.12 are found to tilt 4.6° ′ 0.4° from the c axis along an axis in the a-b plane 20.4° ′ 5° from the a axis. This suggests the Pccn (LTO2) Structure, though the octahedra become somewhat distorted and the more distant atoms do not fit the LTO2 Structure. In contrast, the Local Structure of x = 0.16 does fit the LTO2 Structure and has corresponding tilt values of 3.8° ′ 0.5° and 19.5° ′ 7.5°. The Local Structures for both concentrations are found to be independent of temperature, indicating that the various crystal phase transitions found in diffraction are due to long-range averaging of Local Structure regions with orientational disorder. The Local Structure correlation length appears to be longer than the high-T c coherence length, indicating that the Local Structure is the relevant one when considering the pairing mechanism.
