Extending the Applicability of Exact Nuclear Overhauser Enhancements to Large Proteins and RNA

Distance‐dependent nuclear Overhauser enhancements (NOEs) are one of the most popular and important experimental restraints for calculating NMR structures. Despite this, they are mostly employed as semiquantitative upper distance bounds, and this discards the wealth of information that is encoded in...

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Veröffentlicht in:Chembiochem : a European journal of chemical biology Jg. 19; H. 16; S. 1695 - 1701
Hauptverfasser: Nichols, Parker J., Born, Alexandra, Henen, Morkos A., Strotz, Dean, Celestine, Chi N., Güntert, Peter, Vögeli, Beat
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Germany Wiley Subscription Services, Inc 16.08.2018
Schlagworte:
Coding
dynamics
Mathematical analysis
NMR
NMR spectroscopy
Nuclear magnetic resonance
nuclear Overhauser effect
proteasomes
Proteins
Protons
Ribonucleic acid
RNA
dynamics
nuclear Overhauser effect
RNA
NMR spectroscopy
proteasomes
ISSN:1439-4227, 1439-7633, 1439-7633
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Zusammenfassung:Distance‐dependent nuclear Overhauser enhancements (NOEs) are one of the most popular and important experimental restraints for calculating NMR structures. Despite this, they are mostly employed as semiquantitative upper distance bounds, and this discards the wealth of information that is encoded in the cross‐relaxation rate constant. Information that is lost includes exact distances between protons and dynamics that occur on the sub‐millisecond timescale. Our recently introduced exact measurement of the NOE (eNOE) requires little additional experimental effort relative to other NMR observables. So far, we have used eNOEs to calculate multistate ensembles of proteins up to approximately 150 residues. Here, we briefly revisit eNOE methodology and present two new directions for the use of eNOEs: applications to large proteins and RNA. Distance‐dependent NOEs are one of the most popular experimental restraints for calculating NMR structures. Our recently introduced exact measurement of the NOE (eNOE) recovers part of the information that is discarded in commonly used semiquantitative NOE analysis. We revisit eNOE methodology and present two new directions for the use of eNOEs: applications to large proteins and RNA.
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ISSN:1439-4227
1439-7633
1439-7633
DOI:10.1002/cbic.201800237