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Cited by 294

The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.

Nuclear Magnetic Resonance Studies of Biopolymer Dynamics

Palmer, Arthur G., Williams, John, McDermott, Ann·1996·The Journal of Physical Chemistry

Abstract

NMR spectroscopy is a powerful approach for quantitating molecular conformational dynamics at multiple atomic sites and over multiple time scales. Extensive studies by solution and solid-state NMR spectroscopy of spin relaxation and line shapes in biological macromolecules have been performed in order to characterize the amplitudes, time scales, and energetics of intramolecular conformational modes and to elucidate the relationships between conformational dynamics, structure, and function. This review describes NMR spectroscopic methods for investigation of conformational dynamics together with theoretical descriptions appropriate for interpretation and simulation of the techniques, surveys the range of results available from solution and solid state NMR studies of proteins and other biomolecules, and identifies opportunities for further individual and collaborative development of solution and solid state NMR techniques for characterizing the dynamical properties of biological macromolecules.

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Crossref · 10.1021/jp9606117

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Metadata

Authors
Palmer, A. G., Williams, J., & McDermott, A.
Venue
The Journal of Physical Chemistry
Published
1996-01-01
Volume
100
Issue
31
Pages
13293-13310
ISSN
  • 0022-3654 (ISSN-L)
  • 1541-5740
OpenAlex
W2092985709
Cited by
294
References
57
FWCI
9.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Nuclear Magnetic Resonance Studies of Biopolymer Dynamics. https://app.cochat.ai/papers/10.1021/jp9606117
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Palmer, A. G., Williams, J., & McDermott, A. (1996). Nuclear Magnetic Resonance Studies of Biopolymer Dynamics. The Journal of Physical Chemistry. https://doi.org/10.1021/jp9606117

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.