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Revealing the macromolecular targets of complex natural products

Nature Chemistry volume 6, pages 1072–1078 (2014)Cite this article

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Abstract

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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Figure 1: Comparison of the distributions of natural products and drugs in chemical space.
Figure 2: Comparison of the molecular structures in the compound libraries.
Figure 3: Frequently predicted targets of NPDFs.
Figure 4: Virtual fragmentation and pharmacophore alignment of ArcA.
Figure 5: Biochemical analysis of the effects of ArcA on the predicted targets.

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Change history

  • 05 November 2014

    In the version of this Article originally published online, the units of concentration on the x axis in Fig. 5e should have read 'μM'. This error was introduced during production and has been corrected in all versions of the Article.

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Acknowledgements

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).

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Authors and Affiliations

  1. Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology (ETH), Institute of Pharmaceutical Sciences, Vladimir-Prelog-Weg 4, Zürich, 8093, Switzerland

    Daniel Reker, Anna M. Perna, Tiago Rodrigues, Petra Schneider, Michael Reutlinger & Gisbert Schneider

  2. Friedrich-Schiller-Universität Jena, Institut für Pharmazie, Philosophenweg 14, Jena, 07743, Germany

    Bettina Mönch, Andreas Koeberle & Oliver Werz

  3. Goethe-Universität, Institut für Pharmazeutische Chemie, Max-von-Laue-Str. 9, Frankfurt a. M., 60438, Germany

    Christina Lamers, Matthias Gabler & Manfred Schubert-Zsilavecz

  4. Helmholtz Institut für Pharmazeutische Forschung, Helmholtz Zentrum für Infektionsforschung und Pharmazeutische Biotechnologie, Universität des Saarlandes, Saarbrücken, 66041, Germany

    Heinrich Steinmetz & Rolf Müller

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Contributions

D.R., A.M.P., M.R., P.S., T.R. and G.S. developed the target prediction tool and performed the computational experiments. B.M., A.K., C.L., M.G., H.S., M.S-Z. and O.W. conceived and performed the biochemical experiments. H.S. and R.M. contributed ArcA. D.R. and G.S. conceived the investigation and prepared the manuscript, with feedback and contributions from the other authors.

Corresponding author

Correspondence to Gisbert Schneider.

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Competing interests

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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