Direct deduction of chemical class from NMR spectra

Kuhn, Stefan, Cobas, Carlos, Barba, Agustin, Colreavy-Donnelly, Simon, Caraffini, Fabio, Borges, Ricardo Moreira

arXiv.org Artificial Intelligence 

Nuclear Magnetic Resonance (NMR) spectroscopy is an established technique in analytical chemistry. As a result of its rich structural and dynamic information content, it is particularly suitable for compound identification. However, a full elucidation may not always be possible or even necessary since some properties might be achievable directly from the spectra. If this is the case, a prioritisation of substances to be closely investigated for compound assignment can be done in the early stages of a study. A previous example for this idea was demonstrated in [1], where the authors showed that the existence of certain substructures can be concluded from profiles in the spectra. Another potentially useful application is chemical classification. These rely strongly on annotated chemical entities to provide a computable chemical taxonomy based on substructures.

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