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Updated: Jul 3, 2026
14:37
Modeling an Enzyme Active Site using Molecular Visualization Freeware
Published on: December 25, 2021
Evolutionarily conserved substrate substructures for automated annotation of enzyme superfamilies
Ranyee A Chiang1, Andrej Sali, Patricia C Babbitt
1Department of Biopharmaceutical Sciences, California Institute for Quantitative Biosciences, University of California at San Francisco, San Francisco, California, United States of America.
Plos Computational Biology
|August 2, 2008
Summary
Enzyme evolution shows conserved and variable functions. Analyzing enzyme substrate graphs reveals unique patterns for each superfamily, improving function prediction and enzyme engineering strategies.
Area of Science:
- Biochemistry
- Enzyme kinetics
- Evolutionary biology
Background:
- Enzyme evolution influences species adaptation.
- Enzyme function exhibits conserved and variable aspects.
- Conserved functions are difficult to change or broadly applicable; variable functions may be less critical or obsolete.
Purpose of the Study:
- To analyze conservation and variation patterns in enzyme function using substrate graphs.
- To establish conservation patterns typical of enzyme superfamilies.
- To understand the relationship between conserved and reacting substructures within enzyme substrates.
Main Methods:
- Analysis of graph isomorphisms among enzyme substrates for numerous enzyme superfamilies.
- Determination of conserved chemical substructures across all known substrates of a superfamily.
- Identification of reacting substructures within these substrates.
Main Results:
- Substantial variation exists in the proportion of conserved substructures that are reacting across 42 analyzed superfamilies.
- Enzyme superfamilies cannot be easily categorized into discrete groups based on these patterns.
- Conserved and reacting substructure patterns offer information orthogonal to sequence and structural conservation.
Conclusions:
- Enzyme superfamilies require individual analysis for evolutionary studies, function prediction, and engineering.
- Annotating superfamilies with substrate substructure patterns enhances enzyme function prediction accuracy.
- The automated method facilitates large-scale characterization of enzyme superfamilies' functional capabilities.
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