Abstract
Compound identification in complex mixtures by NMR and MS is best achieved through experimental databases (DB) mining. Experimental DB frequently show limitations regarding their completeness, availability or data quality, thus making predicted database (e.g., ISDB, PNMRNP) of increasing common use [1]. Querying large databases may lead to select unlikely structure candidates. Two approaches to dereplication are thus possible: taxonomical filtering (either biological or chemical) of the DB before search or taxonomical scoring of the results after a large-scale search [2]. The present work relies on the former approach. The corresponding dereplication tool involves the selection of the structure set of interest from the largest available structural DB and the prediction of the associated NMR and MS spectral data ([Fig. 1]).
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