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The conformational space of the ribose-phosphate backbone is very complex as it is defined in terms of six torsional angles. To help delimit the RNA backbone conformational preferences, 46 rotamers have been defined in terms of these torsional angles. In the present work, we use the ribose experimental and theoretical 13C' chemical shifts data and machine learning methods to classify RNA backbone conformations into rotamers and families of rotamers. We show to what extent the experimental 13C' chemical shifts can be used to identify rotamers and discuss some problem with the theoretical computations of 13C' chemical shifts.
Pubmed ID: 31656702
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Public depository that collects, annotates, archives, and disseminates important spectral and quantitative data derived from nuclear magnetic resonance spectroscopic investigations of biological macromolecules and metabolites. Provides reference information and maintains a collection of NMR pulse sequences and computer software for biomolecular NMR.
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