Spectral editing of two-dimensional magic-angle-spinning solid-state NMR spectra for protein resonance assignment and structure determination View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-12

AUTHORS

K. Schmidt-Rohr, K. J. Fritzsching, S. Y. Liao, Mei Hong

ABSTRACT

Several techniques for spectral editing of 2D (13)C-(13)C correlation NMR of proteins are introduced. They greatly reduce the spectral overlap for five common amino acid types, thus simplifying spectral assignment and conformational analysis. The carboxyl (COO) signals of glutamate and aspartate are selected by suppressing the overlapping amide N-CO peaks through (13)C-(15)N dipolar dephasing. The sidechain methine (CH) signals of valine, lecuine, and isoleucine are separated from the overlapping methylene (CH(2)) signals of long-chain amino acids using a multiple-quantum dipolar transfer technique. Both the COO and CH selection methods take advantage of improved dipolar dephasing by asymmetric rotational-echo double resonance (REDOR), where every other π-pulse is shifted from the center of a rotor period t(r) by about 0.15 t(r). This asymmetry produces a deeper minimum in the REDOR dephasing curve and enables complete suppression of the undesired signals of immobile segments. Residual signals of mobile sidechains are positively identified by dynamics editing using recoupled (13)C-(1)H dipolar dephasing. In all three experiments, the signals of carbons within a three-bond distance from the selected carbons are detected in the second spectral dimension via (13)C spin exchange. The efficiencies of these spectral editing techniques range from 60 % for the COO and dynamic selection experiments to 25 % for the CH selection experiment, and are demonstrated on well-characterized model proteins GB1 and ubiquitin. More... »

PAGES

343-353

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10858-012-9676-8

DOI

http://dx.doi.org/10.1007/s10858-012-9676-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1051518192

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23053913


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RDF/XML is a standard XML format for linked data.

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