Nuclear magnetic resonance spectroscopy of carbohydrates

This method allows the scientists to elucidate structure of monosaccharides, oligosaccharides, polysaccharides, glycoconjugates and other carbohydrate derivatives from synthetic and natural sources.

Carbon-13 NMR overcomes this disadvantage by larger range of chemical shifts and special techniques allowing to block carbon-proton spin coupling, thus making all carbon signals high and narrow singlets distinguishable from each other.

The typical ranges of specific carbohydrate carbon chemical shifts in the unsubstituted monosaccharides are: Direct carbon-proton coupling constants are used to study the anomeric configuration of a sugar.

Vicinal heteronuclear H-C-O-C coupling constants are used to study torsional angles along glycosidic bond between sugars or along exocyclic fragments, thus revealing a molecular conformation.

Sugar rings are relatively rigid molecular fragments, thus vicinal proton-proton couplings are characteristic: NOEs are sensitive to interatomic distances, allowing their usage as a conformational probe, or proof of a glycoside bond formation.

[1] They include: Growing computational power allows usage of thorough quantum-mechanical calculations at high theory levels and large basis sets for refining the molecular geometry of carbohydrates and subsequent prediction of NMR observables using GIAO and other methods with or without solvent effect account.

Heteronuclear NMR techniques in carbohydrate studies, and typical intra-residue (red) and inter-residue (blue) atoms that they link each to other.
Homonuclear NMR techniques in carbohydrate studies, and typical intra-residue (red) and inter-residue (blue) atoms that they link each to other.
Approximate scheme of NMR (blue) and other (green) techniques applied to carbohydrate structure elucidation, and information obtained (in boxes)
Comparative prediction of the 13C NMR spectrum of sucrose using various methods. Experimental spectrum is in the middle. Upper spectrum (black) was obtained by empirical routine. Lower spectra (red and green) were obtained by quantum-chemical calculations in PRIRODA and GAUSSIAN respectively. Included information: used theory level/basis set/solvent model, accuracy of prediction (linear correlation factor and root mean square deviation), calculation time on personal computer (blue).