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A Web Tool for Generating High Quality Machine-readable Biological Pathways
Published on: February 8, 2017
Automatic assignment of reaction operators to enzymatic reactions
Markus Leber1, Volker Egelhofer, Ida Schomburg
1Institute for Biochemistry, University of Cologne, Zülpicher Strasse 47, Germany.
Bioinformatics (Oxford, England)
|September 29, 2009
Summary
This study introduces a new method using the Dugundji-Ugi model to automatically classify enzymes based on their electron shift patterns. This approach simplifies enzyme classification by analyzing reaction matrices derived from chemical structures.
Area of Science:
- Biochemistry
- Computational Biology
- Enzymology
Background:
- Enzyme classification relies on a complex numerical scheme by the IUBMB.
- Manual analysis and frequent system updates are needed due to the complexity of enzymatic reactions.
- Current enzyme classification requires expert knowledge and is prone to manual errors.
Purpose of the Study:
- To develop an automated system for enzyme classification.
- To simplify the complex enzyme classification system.
- To objectively analyze biochemical reactions using electron shift patterns.
Main Methods:
- Utilized the Dugundji-Ugi model to code biochemical reactions based on electron shift patterns.
- Developed a program to automatically calculate reaction matrices from substrate and product structures.
- Employed a novel strategy for maximal common substructure determination for accurate atom mapping.
Main Results:
- Successfully tested the system on a wide range of enzymatic reactions, covering all EC classification sub-subclasses.
- Identified 147 distinct reaction operators, with 121 unique to specific EC sub-subclasses.
- Discovered 26 reaction operators representing groups of enzymes with highly similar reaction mechanisms.
Conclusions:
- The Dugundji-Ugi model effectively defines enzyme groups by unique reaction cores based on electron shifts.
- The developed system offers a rational and objective pre-classification for enzymes.
- This approach provides a new perspective on understanding and categorizing biochemical reactions.
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