Relaxation in nuclear magnetic resonance is a powerful method for obtaining spatially
resolved, timescale-specific dynamics information about molecular systems. However,
dynamics in biomolecular systems are generally too complex to be fully characterized
based on NMR data alone. This is a familiar problem, addressed by the Lipari-Szabo
model-free analysis, a method that captures the full information content of NMR relaxation
data in case all internal motion of a molecule in solution is sufficiently fast. We investigate
model-free analysis, as well as several other approaches, and find that model-free, spectral
density mapping, LeMaster’s approach, and our detector analysis form a class of analysis
methods, for which behavior of the fitted parameters has a well-defined relationship to the
distribution of correlation times of motion, independent of the specific form of that
distribution. In a sense, they are all “model-free.” Of these methods, only detectors are
generally applicable to solid-state NMR relaxation data. We further discuss how detectors
may be used for comparison of experimental data to data extracted from molecular
dynamics simulation, and how simulation may be used to extract details of the dynamics
that are not accessible via NMR, where detector analysis can be used to connect those
details to experiments. We expect that combined methodology can eventually provide
enough insight into complex dynamics to provide highly accurate models of motion, thus
lending deeper insight into the nature of biomolecular dynamics.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:84538 |
| Date | 03 April 2023 |
| Creators | Zumpfe, Kai, Smith, Albert A. |
| Publisher | Frontiers Research Foundation |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 2296-889X, 727553 |
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