Prediction of proton chemical shifts in RNA – Their use in structure refinement and validation View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2001-09

AUTHORS

Jenny A.M.T.C. Cromsigt, Cees W. Hilbers, Sybren S. Wijmenga

ABSTRACT

An analysis is presented of experimental versus calculated chemical shifts of the non-exchangeable protons for 28 RNA structures deposited in the Protein Data Bank, covering a wide range of structural building blocks. We have used existing models for ring-current and magnetic-anisotropy contributions to calculate the proton chemical shifts from the structures. Two different parameter sets were tried: (i) parameters derived by Ribas-Prado and Giessner-Prettre (GP set) [(1981) J. Mol. Struct., 76, 81-92.]; (ii) parameters derived by Case [(1995) J. Biomol. NMR, 6, 341-346]. Both sets lead to similar results. The detailed analysis was carried using the GP set. The root-mean-square-deviation between the predicted and observed chemical shifts of the complete database is 0.16 ppm with a Pearson correlation coefficient of 0.79. For protons in the usually well-defined A-helix environment these numbers are, 0.08 ppm and 0.96, respectively. As a result of this good correspondence, a reliable analysis could be made of the structural dependencies of the 1H chemical shifts revealing their physical origin. For example, a down-field shift of either H2' or H3' or both indicates a high-syn/syn chi-angle. In an A-helix it is essentially the 5'-neighbor that affects the chemical shifts of H5, H6 and H8 protons. The H5, H6 and H8 resonances can therefore be assigned in an A-helix on the basis of their observed chemical shifts. In general, the chemical shifts were found to be quite sensitive to structural changes. We therefore propose that a comparison between calculated and observed 1H chemical shifts is a good tool for validation and refinement of structures derived from NOEs and J-couplings. More... »

PAGES

11-29

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1011914132531

DOI

http://dx.doi.org/10.1023/a:1011914132531

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1051905524

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/11693565


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