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Enhanced NMR discrimination of pharmaceutically relevant molecular crystal forms through fragment-based ab initio chemical shift predictions

Enhanced NMR discrimination of pharmaceutically relevant molecular crystal forms through fragment-based ab initio chemical shift predictions
Enhanced NMR discrimination of pharmaceutically relevant molecular crystal forms through fragment-based ab initio chemical shift predictions
Chemical shift prediction plays an important role in the determination or validation of crystal structures with solid state nuclear magnetic resonance (NMR) spectroscopy. One of the fundamental theoretical challenges lies in discriminating variations in chemical shifts resulting from different crystallographic environments. Fragment-based electronic structure methods provide an alternative to the widely used plane wave gauge-including projector augmented wave (GIPAW) density functional technique for chemical shift prediction. Fragment methods allow hybrid density functionals to be employed routinely in chemical shift prediction, and we have recently demonstrated appreciable improvements in the accuracy of the predicted shifts when using the hybrid PBE0 functional instead of generalized gradient approximation (GGA) functionals like PBE. Here, we investigate the solid-state 13C and 15N NMR spectra for multiple crystal forms of acetaminophen, phenobarbital, and testosterone. We demonstrate that the use of the hybrid density functional instead of a GGA provides both higher accuracy in the chemical shifts and increased discrimination among the different crystallographic environments. Finally, these results also provide compelling evidence for the transferability of the linear regression parameters mapping predicted chemical shieldings to chemical shifts that were derived in an earlier study.
1528-7483
6479-6493
Hartman, Joshua D.
51cb65a2-8358-49b3-a706-c173475d5aa5
Day, Graeme
e3be79ba-ad12-4461-b735-74d5c4355636
Beran, Gregory B.O.
5aa9cb23-6a38-4037-a878-90a4bf88250e
Hartman, Joshua D.
51cb65a2-8358-49b3-a706-c173475d5aa5
Day, Graeme
e3be79ba-ad12-4461-b735-74d5c4355636
Beran, Gregory B.O.
5aa9cb23-6a38-4037-a878-90a4bf88250e

Hartman, Joshua D., Day, Graeme and Beran, Gregory B.O. (2016) Enhanced NMR discrimination of pharmaceutically relevant molecular crystal forms through fragment-based ab initio chemical shift predictions. Crystal Growth & Design, 16 (11), 6479-6493. (doi:10.1021/acs.cgd.6b01157).

Record type: Article

Abstract

Chemical shift prediction plays an important role in the determination or validation of crystal structures with solid state nuclear magnetic resonance (NMR) spectroscopy. One of the fundamental theoretical challenges lies in discriminating variations in chemical shifts resulting from different crystallographic environments. Fragment-based electronic structure methods provide an alternative to the widely used plane wave gauge-including projector augmented wave (GIPAW) density functional technique for chemical shift prediction. Fragment methods allow hybrid density functionals to be employed routinely in chemical shift prediction, and we have recently demonstrated appreciable improvements in the accuracy of the predicted shifts when using the hybrid PBE0 functional instead of generalized gradient approximation (GGA) functionals like PBE. Here, we investigate the solid-state 13C and 15N NMR spectra for multiple crystal forms of acetaminophen, phenobarbital, and testosterone. We demonstrate that the use of the hybrid density functional instead of a GGA provides both higher accuracy in the chemical shifts and increased discrimination among the different crystallographic environments. Finally, these results also provide compelling evidence for the transferability of the linear regression parameters mapping predicted chemical shieldings to chemical shifts that were derived in an earlier study.

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Accepted/In Press date: 12 September 2016
e-pub ahead of print date: 4 October 2016
Published date: 2 November 2016
Organisations: Chemistry

Identifiers

Local EPrints ID: 400439
URI: http://eprints.soton.ac.uk/id/eprint/400439
ISSN: 1528-7483
PURE UUID: 2dc9b5bb-9688-4f0b-92bb-3a028f2dc7a8
ORCID for Graeme Day: ORCID iD orcid.org/0000-0001-8396-2771

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Date deposited: 16 Sep 2016 10:48
Last modified: 07 Oct 2020 04:03

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