page_title: Nuclear magnetic resonance spectroscopy of carbohydrates
section_title: Simulation of the NMR observables
hierarchical_section_title: Nuclear magnetic resonance spectroscopy of carbohydrates / Carbohydrate NMR databases and tools / Simulation of the NMR observables
caption_attribution_description: English: 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).
context_page_description: Carbohydrate NMR Spectroscopy is the application of nuclear magnetic resonance 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, 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.
context_section_description: Several approaches to simulate NMR observables of carbohydrates has been reviewed. They include:
  Universal statistical database approaches (ACDLabs, Modgraph, etc.)
  Usage of neural networks to refine the predictions
  Regression based methods
  CHARGE
  Carbohydrate-optimized empirical schemes (CSDB/BIOPSEL,CASPER).
  Combined molecular mechanics/dynamics geometry calculation and quantum-mechanical simulation/iteration of NMR observables (PERCH NMR Software)
  ONIOM approaches (optimization of different parts of molecule with different accuracy)
  Ab initio calculations.
  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.
caption: 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).
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