Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

NATURAL PRODUCTS

Predicting the peculiar

Nature Chemical Biology volume 15, pages 761–763 (2019)Cite this article

Subjects

Using knowledge of their evolutionary origin, an automated platform has been developed to provide accurate de novo structural predictions of products from trans-acyltransferase polyketide synthases.

trans-Acyltransferase (trans-AT) polyketide synthases (PKSs) are highly complex molecular machines responsible for the biosynthesis of an exquisite array of structurally diverse, bioactive metabolites. However, many trans-AT PKS biosynthetic gene clusters (BGCs) occur in poorly characterized microbes and often encode unorthodox biosynthetic pathways, making genomics-driven discovery approaches a formidable endeavor. In this issue, Helfrich et al. report the development of a new bio- and chemoinformatics tool to overcome such barriers and bring predictive power to the peculiar world of trans-AT PKSs1.

This is a preview of subscription content, access via your institution

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

Buy

All prices are NET prices.

Fig. 1: Automated structure prediction of a trans-AT PKS product using the TransATor platform.

References

  1. Helfrich, E. J. N. et al. Nat. Chem. Biol. https://doi.org/10.1038/s41589-019-0313-7 (2019).

  2. Piel, J. Proc. Natl. Acad. Sci. USA 99, 14002–14007 (2002).

    Article  CAS  Google Scholar 

  3. Cheng, Y. Q., Tang, G. L. & Shen, B. Proc. Natl. Acad. Sci. USA 100, 3149–3154 (2003).

    Article  CAS  Google Scholar 

  4. Helfrich, E. J. N. & Piel, J. Nat. Prod. Rep. 33, 231–316 (2016).

    Article  CAS  Google Scholar 

  5. Kosol, S., Jenner, M., Lewandowski, J. R. & Challis, G. L. Nat. Prod. Rep. 35, 1097–1109 (2018).

    Article  CAS  Google Scholar 

  6. Nguyen, T. et al. Nat. Biotechnol. 26, 225–233 (2008).

    Article  CAS  Google Scholar 

  7. Eddy, S. R. Bioinformatics 14, 755–763 (1998).

    Article  CAS  Google Scholar 

  8. Moldenhauer, J., Chen, X. H., Borriss, R. & Piel, J. Angew. Chem. Int. Ed. Engl. 46, 8195–8197 (2007).

    Article  CAS  Google Scholar 

  9. Blin, K. et al. Nucleic Acids Res. 45, W36–W41 (2017).

    Article  CAS  Google Scholar 

  10. Skinnider, M. A., Merwin, N. J., Johnston, C. W. & Magarvey, N. A. Nucleic Acids Res. 45, W49–W54 (2017).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Chemistry, University of Warwick, Coventry, UK

    Matthew Jenner

Authors
  1. Matthew Jenner
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthew Jenner.

Ethics declarations

Competing interests

The author declares no competing interests.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Jenner, M. Predicting the peculiar. Nat Chem Biol 15, 761–763 (2019). https://doi.org/10.1038/s41589-019-0324-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41589-019-0324-4

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing