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Easy Structural Dereplication of Natural Products by Means of Predicted Carbon‐13 Nuclear Magnetic Resonance Spectroscopy Data

The present article reports the creation and usage of a general natural product database for the structural dereplication of natural products. This database, acd_lotusv7, derives from the LOTUS natural products database as the sole source of chemical structures. Database construction also relies on...

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Bibliographic Details
Published in:Chemistry methods 2023-04, Vol.3 (4), p.n/a
Main Authors: Kuhn, Stefan, Nuzillard, Jean‐Marc
Format: Article
Language:English
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Summary:The present article reports the creation and usage of a general natural product database for the structural dereplication of natural products. This database, acd_lotusv7, derives from the LOTUS natural products database as the sole source of chemical structures. Database construction also relies on the commercial “ACD/C+H Predictors and DB” software for the prediction of the carbon‐13 nuclear magnetic resonance (NMR) spectral data associated with structures. The linkage of each natural compound with a Wikidata resource identifier already present in LOTUS accelerates the access to the primary literature data such as biologic origin and bibliographic references. The open source nmrshiftdb2 web interface and search engine provide a simple and free way to retrieve compound structures stored in acd_lotusv7 from carbon‐13 data and to analyze search results. Dereplication is illustrated by the easy and free retrieval of the structure of three natural compounds of low, medium, and high complexity from published lists of carbon‐13 NMR chemical shifts. The quick identification of known low molecular weight organic compounds of natural origin by means of 13C NMR data is made easy by the querying of the acd_lotusv7 database that includes structures from the LOTUS database and ACD/Labs chemical shift predictions. The open source nmrshiftdb2 web interface at https://nmrshiftdb.nmr.uni‐koeln.de provides a simple and free way to retrieve compounds from acd_lotusv7 and to analyze search results.
ISSN:2628-9725
2628-9725
DOI:10.1002/cmtd.202200054