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Atomic-level structure determination of amorphous molecular solids by NMR

Author

Listed:
  • Manuel Cordova

    (École Polytechnique Fédérale de Lausanne (EPFL)
    École Polytechnique Fédérale de Lausanne (EPFL))

  • Pinelopi Moutzouri

    (École Polytechnique Fédérale de Lausanne (EPFL))

  • Sten O. Nilsson Lill

    (Pharmaceutical Sciences, R&D, AstraZeneca)

  • Alexander Cousen

    (Pharmaceutical Sciences, R&D, AstraZeneca)

  • Martin Kearns

    (Pharmaceutical Sciences, R&D, AstraZeneca)

  • Stefan T. Norberg

    (Pharmaceutical Technology & Development, Operations, AstraZeneca)

  • Anna Svensk Ankarberg

    (Pharmaceutical Technology & Development, Operations, AstraZeneca)

  • James McCabe

    (Pharmaceutical Sciences, R&D, AstraZeneca)

  • Arthur C. Pinon

    (University of Gothenburg)

  • Staffan Schantz

    (Pharmaceutical Technology & Development, Operations, AstraZeneca)

  • Lyndon Emsley

    (École Polytechnique Fédérale de Lausanne (EPFL)
    École Polytechnique Fédérale de Lausanne (EPFL))

Abstract

Structure determination of amorphous materials remains challenging, owing to the disorder inherent to these materials. Nuclear magnetic resonance (NMR) powder crystallography is a powerful method to determine the structure of molecular solids, but disorder leads to a high degree of overlap between measured signals, and prevents the unambiguous identification of a single modeled periodic structure as representative of the whole material. Here, we determine the atomic-level ensemble structure of the amorphous form of the drug AZD4625 by combining solid-state NMR experiments with molecular dynamics (MD) simulations and machine-learned chemical shifts. By considering the combined shifts of all 1H and 13C atomic sites in the molecule, we determine the structure of the amorphous form by identifying an ensemble of local molecular environments that are in agreement with experiment. We then extract and analyze preferred conformations and intermolecular interactions in the amorphous sample in terms of the stabilization of the amorphous form of the drug.

Suggested Citation

  • Manuel Cordova & Pinelopi Moutzouri & Sten O. Nilsson Lill & Alexander Cousen & Martin Kearns & Stefan T. Norberg & Anna Svensk Ankarberg & James McCabe & Arthur C. Pinon & Staffan Schantz & Lyndon Em, 2023. "Atomic-level structure determination of amorphous molecular solids by NMR," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40853-2
    DOI: 10.1038/s41467-023-40853-2
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    References listed on IDEAS

    as
    1. Keith T. Butler & Daniel W. Davies & Hugh Cartwright & Olexandr Isayev & Aron Walsh, 2018. "Machine learning for molecular and materials science," Nature, Nature, vol. 559(7715), pages 547-555, July.
    2. Manuel Cordova & Martins Balodis & Albert Hofstetter & Federico Paruzzo & Sten O. Nilsson Lill & Emma S. E. Eriksson & Pierrick Berruyer & Bruno Simões de Almeida & Michael J. Quayle & Stefan T. Norbe, 2021. "Structure determination of an amorphous drug through large-scale NMR predictions," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    3. Federico M. Paruzzo & Albert Hofstetter & Félix Musil & Sandip De & Michele Ceriotti & Lyndon Emsley, 2018. "Chemical shifts in molecular solids by machine learning," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
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