Crystal structure validation of verinurad via proton-detected ultra-fast MAS NMR and machine learning

The recent development of ultra-fast MAS (>100 kHz) provides new opportunities for structural characterization in solids. Here we use NMR crystallography to validate the structure of verinurad, a microcrystalline active pharmaceutical ingredient. To do this, we take advantage of 1H resolution improvement at ultra-fast MAS and use solely 1H-detected experiments and machine learning methods to assign all the experimental proton and carbon chemical shifts. This framework provides a new tool for elucidating chemical information from crystalline samples with limited sample volume and yields remarkably faster acquisition times compared to 13C-detected experiments, without the need to employ dynamic nuclear polarization.

Identifier
Source https://archive.materialscloud.org/record/2024.136
Metadata Access https://archive.materialscloud.org/xml?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:materialscloud.org:2173
Provenance
Creator Torodii, Daria; Holmes, Jacob; Moutzouri, Pinelopi; Nilsson Lill, Sten; Cordova, Manuel; Pinon, Arthur; Grohe, Kristof; Wegner, Sebastian; Putra, Okky Dwichandra; Norberg, Stefan; Welinder, Anette; Schantz, Staffan; Emsley, Lyndon
Publisher Materials Cloud
Publication Year 2024
Rights info:eu-repo/semantics/openAccess; Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode
OpenAccess true
Contact archive(at)materialscloud.org
Representation
Language English
Resource Type Dataset
Discipline Materials Science and Engineering