Natural products have long been a source of useful biological activity for the development of new drugs. Their macromolecular targets are, however, largely unknown, which hampers rational drug design and optimization. Here we present the development and experimental validation of a computational method for the discovery of such targets. The technique does not require three-dimensional target models and may be applied to structurally complex natural products. The algorithm dissects the natural products into fragments and infers potential pharmacological targets by comparing the fragments to synthetic reference drugs with known targets. We demonstrate that this approach results in confident predictions. In a prospective validation, we show that fragments of the potent antitumour agent archazolid A, a macrolide from the myxobacterium Archangium gephyra, contain relevant information regarding its polypharmacology. Biochemical and biophysical evaluation confirmed the predictions. The results obtained corroborate the practical applicability of the computational approach to natural product ‘de-orphaning’.
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We thank the Chemical Computing Group for an MOE research license, Inte:Ligand GmbH for the LigandScout software license and inSili.com LLC for access to the COBRA database and the MOLMAP software. This study was financially supported by the OPO Foundation Zürich and the Deutsche Forschungsgemeinschaft (DFG, FOR1406).
P.S. and G.S. are cofounders of inSili.com LLC, Zürich, and are consultants in the pharmaceutical industry. All the other authors declare no competing financial interests.
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Reker, D., Perna, A., Rodrigues, T. et al. Revealing the macromolecular targets of complex natural products. Nature Chem 6, 1072–1078 (2014). https://doi.org/10.1038/nchem.2095
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