Evidence map›Paper›PMID 31308532›Full record

ArticleNature chemical biology2019

Automated structure prediction of trans-acyltransferase polyketide synthase products.

Eric J N Helfrich, Reiko Ueoka, Alon Dolev, Michael Rust, Roy A Meoded, Agneya Bhushan, Gianmaria Califano, Rodrigo Costa, Muriel Gugger, Christoph Steinbeck and 2 more

Open access · greenAbstract read
In one paragraph

Article in Nature chemical biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed
14.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

59 citing papers in PubMed, 131 citations in OpenAlex.

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  16. Evolution-guided engineering ofScience (New York, N.Y.) · 2024
    Article
  17. Article
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  19. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 5 institutions in 5 countries.

Eric J N HelfrichInstitute of Microbiology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland.
Reiko UeokaInstitute of Microbiology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland.
Alon DolevInstitute of Microbiology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland.
Michael RustInstitute of Microbiology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland.
Roy A MeodedInstitute of Microbiology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland.
Agneya BhushanInstitute of Microbiology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland.
Gianmaria CalifanoCentre of Marine Sciences, University of Algarve, Faro, Portugal.
Rodrigo CostaCentre of Marine Sciences, University of Algarve, Faro, Portugal.ORCID http://orcid.org/0000-0002-5932-4101
Muriel GuggerInstitut Pasteur, Collection des Cyanobactéries, Paris, France.ORCID http://orcid.org/0000-0001-6728-1976
Christoph SteinbeckInstitute for Inorganic and Analytical Chemistry, Friedrich-Schiller-Universität Jena, Jena, Germany.ORCID http://orcid.org/0000-0001-6966-0814
Pablo MorenoEuropean Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton Cambridge, UK. pmoreno@ebi.ac.uk.
Jörn PielInstitute of Microbiology, Eidgenössische Technische Hochschule Zürich, Zurich, Switzerland. jpiel@ethz.ch.ORCID http://orcid.org/0000-0002-2282-8154
Board of the Swiss Federal Institutes of Technology · CHEuropean Bioinformatics Institute · GBInstitut Pasteur · FRUniversity of Algarve · PTUniversity of Lisbon · PT

Funding

European Research Council 742739
6 · The paper itself

Abstract

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.

Indexed as

Amino Acid SequenceAnimalsBacteriaBacterial ProteinsBiological ProductsModels, ChemicalPhylogenyPolyketidesPolyketide SynthasesPoriferaProtein DomainsSubstrate SpecificityBacterial ProteinsBiological ProductsPolyketidesPolyketide Synthases

Identifiers

PMID31308532
PMCPMC6642696
OpenAlexW2961626135

What OpenQuestion holds

Textmetadata
LicenceTDM
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.