Evidence map›Paper›PMID 18670595›Full record

ArticlePLoS computational biology2008

Evolutionarily conserved substrate substructures for automated annotation of enzyme superfamilies.

Ranyee A Chiang, Andrej Sali, Patricia C Babbitt

Abstract read
In one paragraph

Article in PLoS computational biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. The evolution of enzyme function in the isomerases.Current opinion in structural biology · 2014
    Review
  6. Article
  7. Review
  8. Accuracy of functional surfaces on comparatively modeled protein structures.Journal of structural and functional genomics · 2011
    Article
  9. Toward mechanistic classification of enzyme functions.Current opinion in chemical biology · 2011
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Review
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

3 authors.

Ranyee A ChiangDepartment of Biopharmaceutical Sciences, California Institute for Quantitative Biosciences, University of California at San Francisco, San Francisco, California, United States of America.
Andrej Sali
Patricia C Babbitt

Funding

Theoretical and Computational ApproachesP01GM071790 · NIGMS · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI RAUSHEL, FRANK M. · 2004 to 2013
$15.5M
Laying the Foundation of Genomic EnzymologyR01GM060595 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BABBITT, PATRICIA CLEMENT · 2000 to 2018
$5.4M
NIGMS NIH HHS GM60595NIGMS NIH HHS P01 GM071790NIGMS NIH HHS P01 GM71790NIGMS NIH HHS R01 GM060595
6 · The paper itself

Abstract

The evolution of enzymes affects how well a species can adapt to new environmental conditions. During enzyme evolution, certain aspects of molecular function are conserved while other aspects can vary. Aspects of function that are more difficult to change or that need to be reused in multiple contexts are often conserved, while those that vary may indicate functions that are more easily changed or that are no longer required. In analogy to the study of conservation patterns in enzyme sequences and structures, we have examined the patterns of conservation and variation in enzyme function by analyzing graph isomorphisms among enzyme substrates of a large number of enzyme superfamilies. This systematic analysis of substrate substructures establishes the conservation patterns that typify individual superfamilies. Specifically, we determined the chemical substructures that are conserved among all known substrates of a superfamily and the substructures that are reacting in these substrates and then examined the relationship between the two. Across the 42 superfamilies that were analyzed, substantial variation was found in how much of the conserved substructure is reacting, suggesting that superfamilies may not be easily grouped into discrete and separable categories. Instead, our results suggest that many superfamilies may need to be treated individually for analyses of evolution, function prediction, and guiding enzyme engineering strategies. Annotating superfamilies with these conserved and reacting substructure patterns provides information that is orthogonal to information provided by studies of conservation in superfamily sequences and structures, thereby improving the precision with which we can predict the functions of enzymes of unknown function and direct studies in enzyme engineering. Because the method is automated, it is suitable for large-scale characterization and comparison of fundamental functional capabilities of both characterized and uncharacterized enzyme superfamilies.

Indexed as

Evolution, MolecularAmino Acid SequenceAnimalsCatalysisCluster AnalysisComputational BiologyConserved SequenceDatabases, ProteinEnzymesHumansPattern Recognition, AutomatedProtein BindingProtein Interaction Domains and MotifsSequence AlignmentStructural Homology, ProteinStructure-Activity RelationshipEnzymes

Identifiers

PMID18670595
PMCPMC2453236

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Registered trials

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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.