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This report describes the first application of the novel NMR-based machine learning tool "Small Molecule Accurate Recognition Technology" (SMART 2.0) for mixture analysis and subsequent accelerated discovery and characterization of new natural products. The concept was applied to the extract of a filamentous marine cyanobacterium known to be a prolific producer of cytotoxic natural products. This environmental Symploca extract was roughly fractionated, and then prioritized and guided by cancer cell cytotoxicity, NMR-based SMART 2.0, and MS2-based molecular networking. This led to the isolation and rapid identification of a new chimeric swinholide-like macrolide, symplocolide A, as well as the annotation of swinholide A, samholides A-I, and several new derivatives. The planar structure of symplocolide A was confirmed to be a structural hybrid between swinholide A and luminaolide B by 1D/2D NMR and LC-MS2 analysis. A second example applies SMART 2.0 to the characterization of structurally novel cyclic peptides, and compares this approach to the recently appearing "atomic sort" method. This study exemplifies the revolutionary potential of combined traditional and deep learning-assisted analytical approaches to overcome longstanding challenges in natural products drug discovery.

Three decahydroisoquinoline alkaloids, lepadins I-K, were isolated from a specimen of Didemnum sp. collected in the Bahamas. The structures of the new compounds were assigned by an integrated analysis of MS, IR, and 1H, 13C, and 2D NMR spectra. Like previously reported lepadins, the structures of the new compounds contain a decahydroquinoline heterocyclic core in lepadin I, and a new variation, an octahydroquinoline in lepadin J, but differ from earlier reported compounds by acylation of the 3-hydroxyl group by a rare 3'-methylthioacrylate. The absolute configuration of lepadin I was solved by interpretation of NOE measurements, and exciton coupled circular dichroism (ECCD) of the corresponding N- p-bromobenzoyl derivative. The latter constitutes a general method for determination of absolute configuration of the entire lepadin family. The configuration of the remote side-chain secondary carbinol was solved by the modified Mosher's esters method. Lepadin I inhibited butyrylcholineesterase (BuChE, IC50 3.1 μM), but only weakly inhibited acetylcholineesterase (AChE) (10% at 100 μM).

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Many halogenases interchangeably incorporate chlorine and bromine into organic molecules. On the basis of an unsubstantiated report that the alga Ochromonas danica, a prodigious producer of chlorosulfolipids, was able to produce bromosulfolipids, we have investigated the promiscuity of its halogenases toward bromine incorporation. We have found that bromosulfolipids are produced with the exact positional and stereochemical selectivity as in the chlorosulfolipid danicalipin A when this alga is grown under modified conditions containing excess bromide ion.