Collections of natural extracts hold potential for the discovery of novel natural products with original modes of action. The prioritization of extracts from collections remains challenging due to the lack of a workflow that combines multiple-source information to facilitate the data interpretation. Results from different analytical techniques and literature reports need to be organized, processed, and interpreted to enable optimal decision-making for extracts prioritization. Here, we introduce , a computational tool that highlights the structural novelty potential within extracts, considering untargeted mass spectrometry data, spectral annotation, and literature reports. Based on this information, calculates multiple scores that inform their structural potential. Thus, has the potential to accelerate new natural products discovery. was applied to a set of plants from the Celastraceae family as a proof of concept. The (Willd.) A.C.Sm roots extract was highlighted as a promising source of potentially novel compounds. Its phytochemical investigation resulted in the isolation and characterization of thirteen new dihydro--agarofuran sesquiterpenes, five of them presenting a new 9-oxodihydro--agarofuran base scaffold.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9692083 | PMC |
| http://dx.doi.org/10.3389/fmolb.2022.1028334 | DOI Listing |
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