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An introduction to NMR-based approaches for measuring protein dynamics
Open accessAbstract
Proteins are inherently flexible at ambient temperature. At equilibrium, they are characterized by a set of conformations that undergo continuous exchange within a hierarchy of spatial and temporal scales ranging from nanometers to micrometers and femtoseconds to hours. Dynamic properties of proteins are essential for describing the structural bases of their biological functions including catalysis, binding, regulation and cellular structure. Nuclear magnetic resonance (NMR) spectroscopy represents a powerful technique for measuring these essential features of proteins. Here we provide an introduction to NMR-based approaches for studying protein dynamics, highlighting eight distinct methods with recent examples, contextualized within a common experimental and analytical framework. The selected methods are (1) Real-time NMR, (2) Exchange spectroscopy, (3) Lineshape analysis, (4) CPMG relaxation dispersion, (5) Rotating frame relaxation dispersion, (6) Nuclear spin relaxation, (7) Residual dipolar coupling, (8) Paramagnetic relaxation enhancement.
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A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Estimating the Dimension of a Model
Schwarz, G. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344136 · Cited by 47,033
On Information and Sufficiency
Kullback, S., & Leibler, R. A. (1951) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177729694 · Cited by 20,193
Addelman, S. (1979) · Technometrics · doi:10.1080/00401706.1979.10489788 · Cited by 6,750
Effects of Diffusion on Free Precession in Nuclear Magnetic Resonance Experiments
Carr, H. Y., & Purcell, E. M. (1954) · Physical Review · doi:10.1103/physrev.94.630 · Cited by 6,466
Resonance Absorption by Nuclear Magnetic Moments in a Solid
Purcell, E. M., Torrey, H. C., & Pound, R. V. (1946) · Physical Review · doi:10.1103/physrev.69.37 · Cited by 6,053
Modified Spin-Echo Method for Measuring Nuclear Relaxation Times
Meiboom, S., & Gill, D. (1958) · Review of Scientific Instruments · doi:10.1063/1.1716296 · Cited by 6,022
Investigation of exchange processes by two-dimensional NMR spectroscopy
Jeener, J., Meier, B. H., Bachmann, P., & Ernst, R. R. (1979) · The Journal of Chemical Physics · doi:10.1063/1.438208 · Cited by 4,749
Lipari, G., & Szabo, A. (1982) · Journal of the American Chemical Society · doi:10.1021/ja00381a009 · Cited by 3,777
Bloch, F. (1946) · Physical Review · doi:10.1103/physrev.70.460 · Cited by 3,676
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Metadata
- Authors
- Kleckner, I. R., & Foster, M. P.
- Venue
- Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics
- Publisher
- Elsevier BV
- Published
- 2011-08
- Volume
- 1814
- Issue
- 8
- Pages
- 942-968
- ISSN
- 1570-9639 (ISSN-L)
- OpenAlex
- W2141218040
- Cited by
- 561
- References
- 168
- FWCI
- 5.94
- Type
- journal article
- Language
- en
- Open access
- green
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