Classification of RNA backbone conformations into rotamers using 13C' chemical shifts: Exploring how far we can go

Alejandro A. Icazatti*, Juan M. Loyola, Igal Szleifer, Jorge A. Vila, Osvaldo A. Martin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article number7904
JournalPeerJ
Volume2019
Issue number10
DOIs
StatePublished - 2019

Keywords

  • Chemical shifts
  • DFT
  • Machine learning
  • RNA
  • Rotamers

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

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