Revealing the macromolecular targets of complex natural products.
Published
Journal Article
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'.
Full Text
Duke Authors
Cited Authors
- Reker, D; Perna, AM; Rodrigues, T; Schneider, P; Reutlinger, M; Mönch, B; Koeberle, A; Lamers, C; Gabler, M; Steinmetz, H; Müller, R; Schubert-Zsilavecz, M; Werz, O; Schneider, G
Published Date
- December 2014
Published In
Volume / Issue
- 6 / 12
Start / End Page
- 1072 - 1078
PubMed ID
- 25411885
Pubmed Central ID
- 25411885
Electronic International Standard Serial Number (EISSN)
- 1755-4349
International Standard Serial Number (ISSN)
- 1755-4330
Digital Object Identifier (DOI)
- 10.1038/nchem.2095
Language
- eng