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Kallopterolides A–I (1–9), a family of nine diterpenoids possessing either a cleaved pseudopterane or a severed cembrane skeleton, along with several known compounds were isolated from the Caribbean Sea plume Antillogorgia kallos. The structures and relative configurations of 1–9 were characterized by analysis of HR-MS, IR, UV, and NMR spectroscopic data in addition to computational methods and side-by-side comparisons with published NMR data of related congeners. An investigation was conducted as to the potential of the kallopterolides as plausible in vitro anti-inflammatory, antiprotozoal, and antituberculosis agents. 

Excited State Intramolecular Proton Transfer (ESIPT), originally discovered and explored in depth in a number of extensive photophysical studies, is more recently rediscovered as a powerful synthetic tool, offering rapid access to complex polyheterocycles. In our prior work we have employed ESIPT in aromatic o-keto amines and amides, leading to diverse primary photoproducts—complex quinolinols or azacanes possessing a fused lactam moiety—which could additionally be modified in short, high-yielding postphotochemical reactions to further grow complexity of the heterocyclic core scaffold and/or to decorate it with additional functional groups. Given that sulfonamides are generally known as privileged substructures, in this study we pursued two goals: (i) To explore whether sulfonamides could behave as proton donors in the context of ESIPT-initiated photoinduced reactions; (ii) To assess the scope of subsequent complexity-building photochemical and postphotochemical steps, which give access to polyheterocyclic molecular cores with fused cyclic sulfonamide moieties. In this work we show that this is indeed the case. Simple sulfonamide-containing photoprecursors produced the sought-after heterocyclic products in experimentally simple photochemical reactions accompanied by significant step-normalized complexity increases as corroborated by the Böttcher complexity scores. 

Mostly covering 2018 to 2022 This article describes a personal selection of recent misassigned structures of natural products and their revision with the aid of DU8ML, a machine learning-augmented DFT computational method for fast and accurate calculations of solution NMR chemical shifts and spin–spin coupling constants.