Evidence map›Paper›PMID 24980702›Full record

ArticleeLife2014

Prediction and characterization of enzymatic activities guided by sequence similarity and genome neighborhood networks.

Suwen Zhao, Ayano Sakai, Xinshuai Zhang, Matthew W Vetting, Ritesh Kumar, Brandan Hillerich, Brian San Francisco, Jose Solbiati, Adam Steves, Shoshana Brown and 7 more

Abstract read
In one paragraph

Article in eLife, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed
–field-weighted citation impact
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

57 citing papers in PubMed.

  1. Article
  2. Marine life science & technology · 2025
    Article
  3. Proteome-wide bioinformatic annotation and functional validation of the monotopic phosphoglycosyl transferase superfamily.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 3 Biotech · 2021
    Review
  14. Review
  15. Review
  16. Discovery of novel pathways for carbohydrate metabolism.Current opinion in chemical biology · 2021
    Review
  17. Article
  18. Article
  19. Article
  20. Article
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

17 authors.

Suwen ZhaoDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States.
Ayano SakaiInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, United States.
Xinshuai ZhangInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, United States.
Matthew W VettingDepartment of Biochemistry, Albert Einstein College of Medicine, New York, United States.
Ritesh KumarInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, United States.
Brandan HillerichDepartment of Biochemistry, Albert Einstein College of Medicine, New York, United States.
Brian San FranciscoInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, United States.
Jose SolbiatiInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, United States.
Adam StevesDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States.
Shoshana BrownDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States.
Eyal AkivaDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States.
Alan BarberDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States.
Ronald D SeidelDepartment of Biochemistry, Albert Einstein College of Medicine, New York, United States.
Patricia C BabbittDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States.
Steven C AlmoDepartment of Biochemistry, Albert Einstein College of Medicine, New York, United States.
John A GerltInstitute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, United States.
Matthew P JacobsonDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States.

Funding

WORD PROCESSORP30CA013330 · NCI · YESHIVA UNIVERSITY · PI THOMAS E ROHAN · 1985 to 2026
$111.2M
SUBPROJECT 5U54GM074945 · NIGMS · SGX PHARMACEUTICALS, INC. · PI BURLEY, STEPHEN KEVIN · 2005 to 2009
$46.2M
Core H: MicrobiologyU54GM093342 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI CRONAN, JOHN E. · 2010 to 2015
$34.6M
The NYSGRC: A Large Scale Center for PSI:BiologyU54GM094662 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI ALMO, STEVEN C. · 2010 to 2014
$32.6M
Theoretical and Computational ApproachesP01GM071790 · NIGMS · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI RAUSHEL, FRANK M. · 2004 to 2013
$15.5M
Resource for Biocomputing Visualization and InformaticsP41GM103311 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 2012 to 2017
$8.2M
NCI NIH HHS P30 CA013330NIGMS NIH HHS P01 GM071790NIGMS NIH HHS P01GM071790NIGMS NIH HHS P41 GM103311NIGMS NIH HHS P41-GM103311NIGMS NIH HHS U54 GM074945NIGMS NIH HHS U54GM074945NIGMS NIH HHS U54 GM093342NIGMS NIH HHS U54GM093342NIGMS NIH HHS U54 GM094662NIGMS NIH HHS U54GM094662
6 · The paper itself

Abstract

Metabolic pathways in eubacteria and archaea often are encoded by operons and/or gene clusters (genome neighborhoods) that provide important clues for assignment of both enzyme functions and metabolic pathways. We describe a bioinformatic approach (genome neighborhood network; GNN) that enables large scale prediction of the in vitro enzymatic activities and in vivo physiological functions (metabolic pathways) of uncharacterized enzymes in protein families. We demonstrate the utility of the GNN approach by predicting in vitro activities and in vivo functions in the proline racemase superfamily (PRS; InterPro IPR008794). The predictions were verified by measuring in vitro activities for 51 proteins in 12 families in the PRS that represent ∼85% of the sequences; in vitro activities of pathway enzymes, carbon/nitrogen source phenotypes, and/or transcriptomic studies confirmed the predicted pathways. The synergistic use of sequence similarity networks3 and GNNs will facilitate the discovery of the components of novel, uncharacterized metabolic pathways in sequenced genomes.

Indexed as

Genome, BacterialAlgorithmsAmino Acid IsomerasesComputational BiologyCrystallography, X-RayMagnetic Resonance SpectroscopyMass SpectrometryMetabolic Networks and PathwaysMolecular ConformationMolecular Sequence DataMultigene FamilyPlasmidsRNASpectrometry, Mass, Electrospray IonizationTranscription, GeneticAmino Acid Isomerasesproline racemaseRNAbiochemistryfunctional assignmentgenome neighborhood networksequence similarity network

Identifiers

PMID24980702
PMCPMC4113996

What OpenQuestion holds

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Read underepoch 390

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.