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De Novo Crystal Structure Determination from Machine Learned Chemical Shifts.

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.

SUBMITTER: Balodis M

PROVIDER: S-EPMC9052749 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

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<i>De Novo</i> Crystal Structure Determination from Machine Learned Chemical Shifts.

Balodis Martins M Cordova Manuel M Hofstetter Albert A Day Graeme M GM Emsley Lyndon L

Journal of the American Chemical Society 20220413 16

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 usin ...[more]

PMID: 35416661

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