Carbohydrate NMR spectroscopy is the application of nuclear magnetic resonance (NMR) spectroscopy to structural and conformational analysis of carbohydrates. This method allows the scientists to elucidate structure of monosaccharides, oligosaccharides, polysaccharides, glycoconjugates and other carbohydrate derivatives from synthetic and natural sources. Among structural properties that could be determined by NMR are primary structure (including stereochemistry), saccharide conformation, stoichiometry of substituents, and ratio of individual saccharides in a mixture. Modern high field NMR instruments used for carbohydrate samples, typically 500 MHz or higher, are able to run a suite of 1D, 2D, and 3D experiments to determine a structure of carbohydrate compounds.
See main article: Nuclear magnetic resonance.
See main article: chemical shift. Common chemical shift ranges for nuclei within carbohydrate residues are:
In the case of simple mono- and oligosaccharide molecules, all proton signals are typically separated from one another (usually at 500 MHz or better NMR instruments) and can be assigned using 1D NMR spectrum only. However, bigger molecules exhibit significant proton signal overlap, especially in the non-anomeric region (3-4 ppm). 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:
See main article: coupling constant. Direct carbon-proton coupling constants are used to study the anomeric configuration of a sugar.Vicinal proton-proton coupling constants are used to study stereo orientation of protons relatively to the other protons within a sugar ring, thus identifying a monosaccharide.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:
See main article: Nuclear Overhauser effect. NOEs are sensitive to interatomic distances, allowing their usage as a conformational probe, or proof of a glycoside bond formation. It's a common practice to compare calculated to experimental proton-proton NOEs in oligosaccharides to confirm a theoretical conformational map. Calculation of NOEs implies an optimization of molecular geometry.
Relaxivities, nuclear relaxation rates, line shape and other parameters were reported useful in structural studies of carbohydrates.[1]
The following is a list of structural features that can be elucidated by NMR:
Widely known methods of structural investigation, such as mass-spectrometry and X-ray analysis are only limitedly applicable to carbohydrates.[1] Such structural studies, such as sequence determination or identification of new monosaccharides, benefit the most from the NMR spectroscopy.Absolute configuration and polymerization degree are not always determinable using NMR only, so the process of structural elucidation may require additional methods. Although monomeric composition can be solved by NMR, chromatographic and mass-spectroscopic methods provide this information sometimes easier. The other structural features listed above can be determined solely by the NMR spectroscopic methods. The limitation of the NMR structural studies of carbohydrates is that structure elucidation can hardly be automatized and require a human expert to derive a structure from NMR spectra.
Complex glycans possess a multitude of overlapping signals, especially in a proton spectrum. Therefore, it is advantageous to utilize 2D experiments for the assignment of signals.The table and figures below list most widespread NMR techniques used in carbohydrate studies.
| NMR experiment | Description | Information obtained | |
|---|---|---|---|
| 1H 1D | 1D proton spectrum | measurement of couplings, general information, residue identification, basis for carbon spectrum assignment | |
| 13C BB | Proton-decoupled 1D carbon-13 spectrum | detailed information, residue identification, substitution positions | |
| 31P BB, 15N BB | Proton-decoupled 1D heteronuclei spectra | additional information | |
| APT, 13C DEPT | attached proton test, driven enhanced polarization transfer (edited 1D carbon-13 spectrum) | assignment of CH2 groups | |
| 13C Gated, 31P Gated | Proton-coupled 1D carbon-13 and heteronuclei spectra | measurement of heteronuclear couplings, elucidation of anomeric configuration, conformational studies | |
| 1H,1H J-resolved | 2D NMR plot showing J-couplings in second dimension | accurate J-couplings and chemical shift values for crowded spectral regions | |
| 1H DOSY | 2D NMR plot with proton spectra as a function of molecular diffusion coefficient | measurement of diffusion coefficient, estimate of molecular size/weight, spectral separation of different molecules in a mixture | |
| 1H,1H COSY | Proton spin correlation | proton spectrum assignment using vicinal couplings | |
| COSY RCT, COSY RCT2 | Proton spin correlation with one- or two-step relayed coherence transfer | proton spectrum assignment where signals of neighboring vicinal protons overlap | |
| DQF COSY | Double-quantum filtered proton spin correlation | J-coupling magnitudes & number of protons participating in the J-coupling | |
| 1H HD dif | Selective differential homodecoupling | line shape analysis of the overlapped proton signals | |
| TOCSY (HOHAHA) | Total correlation of all protons within a spin system | distinguishing of spin systems of residues | |
| 1D TOCSY | TOCSY of a single signal | extraction of a spin system of a certain residue | |
| NOESY, ROESY | Homonuclear Nuclear Overhauser effect correlation (through space) | revealing of spatially proximal proton pairs, determination of a sequence of residues, determination of averaged conformation | |
| 1H NOE dif | Selective differential NOE measurement | studies of proton spatial contacts | |
| 1H,13C HSQC | Heteronuclear single-quantum coherence, direct proton-carbon spin correlation | carbon spectrum assignment | |
| 1H,31P HSQC | Heteronuclear single-quantum coherence, proton-phosphorus spin correlation | localization of phosphoric acid residues in phosphoglycans | |
| 1H,13C HMBC | Heteronuclear multiple-bond correlation, vicinal proton-carbon spin correlation | determination of residue sequence, acetylation/amidation pattern, confirmation of substitution positions | |
| 1H,X 1D HMBC | HMBC for a single signal | assignment of proton around a certain carbon or heteroatom | |
| 1H,13C HSQC Relay | Implicit carbon-carbon correlation via vicinal couplings of the attached protons | assignment of neighboring carbon atoms | |
| 1H,13C HSQC-TOCSY | Correlation of protons with all carbons within a spin system, and vice versa | assignment of C5 using H6 and solving similar problems, separation of carbon spectrum into subspectra of residues | |
| 1H,X 1D NOE | Heteronuclear NOE measurement | heteronuclear spatial contacts, conformations |
NMR spectroscopic research includes the following steps:
Multiple chemical shift databases and related services have been created to aid structural elucidation of and expert analysis of their NMR spectra. Of them, several informatics tools are dedicated solely to carbohydrates:
Several approaches to simulate NMR observables of carbohydrates has been reviewed.[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. Among combinations of theory level and a basis set reported as sufficient for NMR predictions were B3LYP/6-311G++(2d,2p) and PBE/PBE (see review). It was shown for saccharides that carbohydrate-optimized empirical schemes provide significantly better accuracy (0.0-0.5 ppm per 13C resonance) than quantum chemical methods (above 2.0 ppm per resonance) reported as best for NMR simulations, and work thousands times faster. However, these methods can predict only chemical shifts and perform poor for non-carbohydrate parts of molecules.As a representative example, see figure on the right.