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.

Various algorithms comparing 2D NMR spectra have been explored for their ability to dereplicate natural products as well as determine molecular structures. However, spectroscopic artefacts, solvent effects, and the interactive effect of functional group(s) on chemical shifts combine to hinder their effectiveness. Here, we leveraged Non-Uniform Sampling (NUS) 2D NMR techniques and deep Convolutional Neural Networks (CNNs) to create a tool, SMART, that can assist in natural products discovery efforts. First, an NUS heteronuclear single quantum coherence (HSQC) NMR pulse sequence was adapted to a state-of-the-art nuclear magnetic resonance (NMR) instrument, and data reconstruction methods were optimized, and second, a deep CNN with contrastive loss was trained on a database containing over 2,054 HSQC spectra as the training set. To demonstrate the utility of SMART, several newly isolated compounds were automatically located with their known analogues in the embedded clustering space, thereby streamlining the discovery pipeline for new natural products.

Bastimolide A (1), a polyhydroxy macrolide with a 40-membered ring, was isolated from a new genus of the tropical marine cyanobacterium Okeania hirsuta. This novel macrolide was defined by spectroscopy and chemical reactions to possess one 1,3-diol, one 1,3,5-triol, six 1,5-diols, and one tert-butyl group; however, the relationships of these moieties to one another were obscured by a highly degenerate (1)H NMR spectrum. Its complete structure and absolute configuration were therefore unambiguously determined by X-ray diffraction analysis of the nona-p-nitrobenzoate derivative (1d). Pure bastimolide A (1) showed potent antimalarial activity against four resistant strains of Plasmodium falciparum with IC50 values between 80 and 270 nM, although with some toxicity to the control Vero cells (IC50 = 2.1 μM), and thus represents a potentially promising lead for antimalarial drug discovery. Moreover, rigorous establishment of its molecular arrangement gives fresh insight into the structures and biosynthesis of cyanobacterial polyhydroxymacrolides.