Empirical and DFT GIAO quantum-mechanical methods of 13C chemical shifts prediction: competitors or collaborators?
Article first published online: 27 JAN 2010
Copyright © 2010 John Wiley & Sons, Ltd.
Magnetic Resonance in Chemistry
Volume 48, Issue 3, pages 219–229, March 2010
How to Cite
Elyashberg, M., Blinov, K., Smurnyy, Y., Churanova, T. and Williams, A. (2010), Empirical and DFT GIAO quantum-mechanical methods of 13C chemical shifts prediction: competitors or collaborators?. Magn. Reson. Chem., 48: 219–229. doi: 10.1002/mrc.2571
- Issue published online: 9 FEB 2010
- Article first published online: 27 JAN 2010
- Manuscript Accepted: 30 DEC 2009
- Manuscript Revised: 22 DEC 2009
- Manuscript Received: 23 OCT 2009
- 13C NMR;
- chemical shift prediction;
- HOSE code;
- neural nets
The accuracy of 13C chemical shift prediction by both DFT GIAO quantum-mechanical (QM) and empirical methods was compared using 205 structures for which experimental and QM-calculated chemical shifts were published in the literature. For these structures, 13C chemical shifts were calculated using HOSE code and neural network (NN) algorithms developed within our laboratory. In total, 2531 chemical shifts were analyzed and statistically processed. It has been shown that, in general, QM methods are capable of providing similar but inferior accuracy to the empirical approaches, but quite frequently they give larger mean average error values. For the structural set examined in this work, the following mean absolute errors (MAEs) were found: MAE(HOSE) = 1.58 ppm, MAE(NN) = 1.91 ppm and MAE(QM) = 3.29 ppm. A strategy of combined application of both the empirical and DFT GIAO approaches is suggested. The strategy could provide a synergistic effect if the advantages intrinsic to each method are exploited. Copyright © 2010 John Wiley & Sons, Ltd.