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De novo crystal structure determination from machine learned chemical shifts

De novo crystal structure determination from machine learned chemical shifts
De novo crystal structure determination from machine learned chemical shifts

Determination of the three-dimensional atomic-level structure of powdered solids is one of the key goals in current chemistry. Solid-state NMR chemical shifts can be used to solve this problem, but they are limited by the high computational cost associated with crystal structure prediction methods and density functional theory chemical shift calculations. Here, we successfully determine the crystal structures of ampicillin, piroxicam, cocaine, and two polymorphs of the drug molecule AZD8329 using on-the-fly generated machine-learned isotropic chemical shifts to directly guide a Monte Carlo-based structure determination process starting from a random gas-phase conformation.

NMR crystallography, Polymorphism, crystal structure prediction
0002-7863
7215-7223
Balodis, Martins
f6183671-8917-4643-b0ed-23ab3273c89b
Cordova, Manuel
697bda2d-023b-4597-9362-9073c82ed921
Hofstetter, Albert
ff05c128-e1e1-41ec-95be-b9a8a5737b9b
Day, Graeme M.
e3be79ba-ad12-4461-b735-74d5c4355636
Emsley, Lyndon
3234816a-24e9-44a0-b134-70c09de78257
Balodis, Martins
f6183671-8917-4643-b0ed-23ab3273c89b
Cordova, Manuel
697bda2d-023b-4597-9362-9073c82ed921
Hofstetter, Albert
ff05c128-e1e1-41ec-95be-b9a8a5737b9b
Day, Graeme M.
e3be79ba-ad12-4461-b735-74d5c4355636
Emsley, Lyndon
3234816a-24e9-44a0-b134-70c09de78257

Balodis, Martins, Cordova, Manuel, Hofstetter, Albert, Day, Graeme M. and Emsley, Lyndon (2022) De novo crystal structure determination from machine learned chemical shifts. Journal of the American Chemical Society, 144 (16), 7215-7223. (doi:10.1021/jacs.1c13733).

Record type: Article

Abstract

Determination of the three-dimensional atomic-level structure of powdered solids is one of the key goals in current chemistry. Solid-state NMR chemical shifts can be used to solve this problem, but they are limited by the high computational cost associated with crystal structure prediction methods and density functional theory chemical shift calculations. Here, we successfully determine the crystal structures of ampicillin, piroxicam, cocaine, and two polymorphs of the drug molecule AZD8329 using on-the-fly generated machine-learned isotropic chemical shifts to directly guide a Monte Carlo-based structure determination process starting from a random gas-phase conformation.

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Accepted/In Press date: 30 March 2022
Published date: 13 April 2022
Additional Information: Funding Information: Financial support from the Swiss National Science Foundation grant no. 200020_178860 and the NCCR MARVEL is acknowledged. Publisher Copyright: © 2022 American Chemical Society. All rights reserved.
Keywords: NMR crystallography, Polymorphism, crystal structure prediction

Identifiers

Local EPrints ID: 456446
URI: http://eprints.soton.ac.uk/id/eprint/456446
ISSN: 0002-7863
PURE UUID: d64088e5-e8a1-4ab4-98bb-f1856f91f4ee
ORCID for Graeme M. Day: ORCID iD orcid.org/0000-0001-8396-2771

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Date deposited: 29 Apr 2022 16:41
Last modified: 29 Sep 2022 01:44

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Contributors

Author: Martins Balodis
Author: Manuel Cordova
Author: Albert Hofstetter
Author: Graeme M. Day ORCID iD
Author: Lyndon Emsley

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