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</script>pmid: 27316321
Neutrons scatter quasielastically from stochastic, diffusive processes, such as overdamped vibrations, localized diffusion and transitions between energy minima. In biological systems, such as proteins and membranes, these relaxation processes are of considerable physical interest. We review here recent methodological advances and applications of quasielastic neutron scattering (QENS) in biology, concentrating on the role of molecular dynamics simulation in generating data with which neutron profiles can be unambiguously interpreted. We examine the use of massively-parallel computers in calculating scattering functions, and the application of Markov state modeling. The decomposition of MD-derived neutron dynamic susceptibilities is described, and the use of this in combination with NMR spectroscopy. We discuss dynamics at very long times, including approximations to the infinite time mean-square displacement and nonequilibrium aspects of single-protein dynamics. Finally, we examine how neutron scattering and MD can be combined to provide information on lipid nanodomains. This article is part of a Special Issue entitled "Science for Life" Guest Editor: Dr. Austen Angell, Dr. Salvatore Magazù and Dr. Federica Migliardo.
Magnetic Resonance Spectroscopy, Temperature, Water, Molecular Dynamics Simulation, Crystallography, X-Ray, Elasticity, Markov Chains, Neutron Diffraction, Phosphoglycerate Kinase, Protein Domains, Muramidase, Spin Labels, Biology, Hydrogen
Magnetic Resonance Spectroscopy, Temperature, Water, Molecular Dynamics Simulation, Crystallography, X-Ray, Elasticity, Markov Chains, Neutron Diffraction, Phosphoglycerate Kinase, Protein Domains, Muramidase, Spin Labels, Biology, Hydrogen
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
