Structure determination of an amorphous drug through large-scale NMR predictions


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{
  "id": "770", 
  "metadata": {
    "title": "Structure determination of an amorphous drug through large-scale NMR predictions", 
    "doi": "10.24435/materialscloud:gg-mx", 
    "license": "Creative Commons Attribution 4.0 International", 
    "keywords": [
      "MARVEL/DD1", 
      "SNSF", 
      "machine learning", 
      "molecular dynamics", 
      "Experimental", 
      "NMR"
    ], 
    "contributors": [
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Cordova", 
        "email": "manuel.cordova@epfl.ch", 
        "givennames": "Manuel"
      }, 
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Balodis", 
        "givennames": "Martins"
      }, 
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Hofstetter", 
        "givennames": "Albert"
      }, 
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Paruzzo", 
        "givennames": "Federico"
      }, 
      {
        "affiliations": [
          "Early Product Development and Manufacturing, Pharmaceutical Sciences, R&D, AstraZeneca, Gothenburg, Sweden"
        ], 
        "familyname": "Nilsson Lill", 
        "givennames": "Sten O."
      }, 
      {
        "affiliations": [
          "Early Product Development and Manufacturing, Pharmaceutical Sciences, R&D, AstraZeneca, Gothenburg, Sweden"
        ], 
        "familyname": "Eriksson", 
        "givennames": "Emma S. E."
      }, 
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Berruyer", 
        "givennames": "Pierrick"
      }, 
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Sim\u00f5es de Almeida", 
        "givennames": "Bruno"
      }, 
      {
        "affiliations": [
          "New Modalities and Parenteral Development, Pharmaceutical Technology & Development, Operations, AstraZeneca, Gothenburg, Sweden"
        ], 
        "familyname": "Quayle", 
        "givennames": "Michael J."
      }, 
      {
        "affiliations": [
          "Oral Product Development, Pharmaceutical Technology & Development, Operations, AstraZeneca, Gothenburg, Sweden"
        ], 
        "familyname": "Norberg", 
        "givennames": "Stefan T."
      }, 
      {
        "affiliations": [
          "Oral Product Development, Pharmaceutical Technology & Development, Operations, AstraZeneca, Gothenburg, Sweden"
        ], 
        "familyname": "Svensk Ankarberg", 
        "givennames": "Anna"
      }, 
      {
        "affiliations": [
          "Oral Product Development, Pharmaceutical Technology & Development, Operations, AstraZeneca, Gothenburg, Sweden"
        ], 
        "familyname": "Schantz", 
        "email": "Staffan.Schantz@astrazeneca.com", 
        "givennames": "Staffan"
      }, 
      {
        "affiliations": [
          "Institut des Sciences et Ing\u00e9nierie Chimiques, \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland"
        ], 
        "familyname": "Emsley", 
        "email": "lyndon.emsley@epfl.ch", 
        "givennames": "Lyndon"
      }
    ], 
    "_files": [
      {
        "description": "Detailed description of the files in the dataset", 
        "checksum": "md5:6e2e913b9198e679bc7842bcfd13c230", 
        "size": 10478, 
        "key": "README.md"
      }, 
      {
        "description": "Python notebooks used for data analysis", 
        "checksum": "md5:460f3702015e81f2d2bde0f88290d369", 
        "size": 1384819, 
        "key": "Scripts.zip"
      }, 
      {
        "description": "Figures generated by the Python scripts", 
        "checksum": "md5:077feccf2c4063778983f94768beae7a", 
        "size": 359200, 
        "key": "Figures.zip"
      }, 
      {
        "description": "Raw NMR data", 
        "checksum": "md5:51cf1a14b077222915b89908397d9041", 
        "size": 466540779, 
        "key": "NMR_Experiments.zip"
      }, 
      {
        "description": "CIF files of candidate crystal structures, XRD structure, potential tautomers, and perturbed crystal structure.", 
        "checksum": "md5:057ef7a36ff055313036d94b8a281e34", 
        "size": 47961, 
        "key": "CIFs.zip"
      }, 
      {
        "description": "Chemical shift computation of the candidate crystal structures", 
        "checksum": "md5:f68f06304dd00de678cdd4ddf434653b", 
        "size": 1766568, 
        "key": "HMBI.zip"
      }, 
      {
        "description": "Molecular Dynamics trajectories of amorphous AZD5718 with different water contents", 
        "checksum": "md5:f90aa5f0e1341a01022fc0e9c512dcad", 
        "size": 2909622253, 
        "key": "MD_Snapshots.zip"
      }, 
      {
        "description": "Predicted shieldings for all snapshots of the MD trajectories", 
        "checksum": "md5:2c18832fa57724b5b9a25dd34ad52632", 
        "size": 2444583448, 
        "key": "ML_Shifts.zip"
      }, 
      {
        "description": "Formation energies of molecules in the MD trajectories", 
        "checksum": "md5:44b01089f5d0f7bb01a40910ce800616", 
        "size": 1400681, 
        "key": "DFTB_D3H5.zip"
      }
    ], 
    "references": [
      {
        "type": "Journal reference", 
        "citation": "M. Cordova, M. Balodis, A. Hofstetter, F. Paruzzo, S. O. Nilsson Lill, E. S. E. Eriksson, P. Berruyer, B. Sim\u00f5es de Almeida, M. J. Quayle, S. T. Norberg, A. Svensk Ankarberg, S. Schantz, L. Emsley, (submitted)", 
        "comment": "Paper where the data is discussed"
      }
    ], 
    "conceptrecid": "769", 
    "version": 1, 
    "edited_by": 100, 
    "id": "770", 
    "owner": 339, 
    "mcid": "2021.41", 
    "is_last": true, 
    "status": "published", 
    "description": "Knowledge of the structure of amorphous solids can direct, for example, the optimization of pharmaceutical formulations, but atomic-level structure determination in amorphous molecular solids has so far not been possible. Solid-state NMR is among the most popular methods to characterize amorphous materials, and Molecular Dynamics (MD) simulations can help describe the structure of disordered materials. However, directly relating MD to NMR experiments in molecular solids has been out of reach until now because of the large size of these simulations. Here, using a machine learning model of chemical shifts, we determine the atomic-level structure of the hydrated amorphous drug AZD5718 by combining dynamic nuclear polarization-enhanced solid-state NMR experiments with predicted chemical shifts for MD simulations of large systems. From these amorphous structures we then identify H-bonding motifs and relate them to local intermolecular complex formation energies.", 
    "license_addendum": null, 
    "_oai": {
      "id": "oai:materialscloud.org:770"
    }, 
    "publication_date": "Mar 16, 2021, 12:12:20"
  }, 
  "revision": 6, 
  "updated": "2021-03-16T11:12:20.726009+00:00", 
  "created": "2021-03-05T15:20:27.036848+00:00"
}