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Updated: Jul 8, 2026

Atomic Scale Structural Studies of Macromolecular Assemblies by Solid-state Nuclear Magnetic Resonance Spectroscopy
Published on: September 17, 2017
Isotropic chemical shifts in magic-angle spinning NMR spectra of proteins
Benjamin J Wylie1, Lindsay J Sperling, Chad M Rienstra
1Department of Chemistry, University of Illinois at Urbana-Champaign, 600 South Mathews Avenue, Urbana, IL 61801, USA.
Abstract:
Here we examine the effect of magic-angle spinning (MAS) rate upon lineshape and observed peak position for backbone carbonyl (C') peaks in NMR spectra of uniformly-(13)C,15N-labeled (U-(13)C,15N) solid proteins. 2D N-C' spectra of U-(13)C,15N microcrystalline protein GB1 were acquired at six MAS rates, and the site-resolved C' lineshapes were analyzed by numerical simulations and comparison to spectra from a sparsely labeled sample (derived from 1,3-(13)C-glycerol). Spectra of the U-(13)C,15N sample demonstrate large variations in the signal-to-noise ratio and peak positions, which are absent in spectra of the sparsely labeled sample, in which most 13C' sites do not possess a directly bonded 13CA. These effects therefore are a consequence of rotational resonance, which is a well-known phenomenon. Yet the magnitude of this effect pertaining to chemical shift assignment has not previously been examined. To quantify these effects in high-resolution protein spectra, we performed exact numerical two- and four-spin simulations of the C' lineshapes, which reproduced the experimentally observed features. Observed peak positions differ from the isotropic shift by up to 1.0 ppm, even for MAS rates relatively far (a few ppm) from rotational resonance. Although under these circumstances the correct isotropic chemical shift values may be determined through simulation, systematic errors are minimized when the MAS rate is equivalent to approximately 85 ppm for 13C. This moderate MAS condition simplifies spectral assignment and enables data sets from different labeling patterns and spinning rates to be used most efficiently for structure determination.
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