Automated structure prediction of trans-acyltransferase polyketide synthase products

Eric Helfrich (1) , Reiko Ueoka (1) , Alon Dolev (1) , Michael Rust (1) , Roy Meoded (1) , Agneya Bhushan (1) , Gianmaria Califano (2, 3) , Rodrigo Costa (2, 4) , Muriel Gugger (5) , Christoph Steinbeck (3, 6) , Pablo Moreno (7) , Jörn Piel (1)

1 ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]
2 CCMAR - Centre of Marine Sciences [Faro]
3 Friedrich-Schiller-Universität = Friedrich Schiller University Jena [Jena, Germany]
4 Instituto Superior Técnico, Universidade Técnica de Lisboa
5 Collection des Cyanobactéries
6 EMBL-EBI - European Bioinformatics Institute [Hinxton]
7 European Bioinformatics Institute [Cambridge, UK]

Bacterial trans-acyltransferase polyketide synthases (trans-AT PKSs) are among the most complex known enzymes from secondary metabolism and are responsible for the biosynthesis of highly diverse bioactive polyketides. However, most of these metabolites remain uncharacterized, since trans-AT PKSs frequently occur in poorly studied microbes and feature a remarkable array of non-canonical biosynthetic components with poorly understood functions. As a consequence, genome-guided natural product identification has been challenging. To enable de novo structural predictions for trans-AT PKS-derived polyketides, we developed the trans-AT PKS polyketide predictor (TransATor). TransATor is a versatile bio- and chemoinformatics web application that suggests informative chemical structures for even highly aberrant trans-AT PKS biosynthetic gene clusters, thus permitting hypothesis-based, targeted biotechnological discovery and biosynthetic studies. We demonstrate the applicative scope in several examples, including the characterization of new variants of bioactive natural products as well as structurally new polyketides from unusual bacterial sources.

Domaines: Sciences du Vivant [q-bio]

Eric Helfrich, Reiko Ueoka, Alon Dolev, Michael Rust, Roy Meoded, et al.. Automated structure prediction of trans-acyltransferase polyketide synthase products. Nature Chemical Biology, 2019, 15 (8), pp.813-821. ⟨10.1038/s41589-019-0313-7⟩. ⟨pasteur-03014757⟩