↓ Skip to main content

PLOS

Evolutionarily Conserved Substrate Substructures for Automated Annotation of Enzyme Superfamilies

Overview of attention for article published in PLoS Computational Biology, August 2008
Altmetric Badge

Mentioned by

f1000
1 research highlight platform

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
64 Mendeley
citeulike
6 CiteULike
connotea
1 Connotea
Title
Evolutionarily Conserved Substrate Substructures for Automated Annotation of Enzyme Superfamilies
Published in
PLoS Computational Biology, August 2008
DOI 10.1371/journal.pcbi.1000142
Pubmed ID
Authors

Ranyee A. Chiang, Andrej Sali, Patricia C. Babbitt

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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 8%
Germany 2 3%
United Kingdom 2 3%
Turkey 1 2%
India 1 2%
France 1 2%
Netherlands 1 2%
Mexico 1 2%
Canada 1 2%
Other 2 3%
Unknown 47 73%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 41%
Student > Ph. D. Student 17 27%
Professor > Associate Professor 4 6%
Professor 4 6%
Student > Bachelor 3 5%
Other 10 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 59%
Biochemistry, Genetics and Molecular Biology 7 11%
Chemistry 6 9%
Computer Science 5 8%
Medicine and Dentistry 2 3%
Other 3 5%
Unknown 3 5%