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Paradigms of convergent evolution in enzymes
Ioannis G Riziotis1, Jenny C Kafas1, Gabriel Ong1
1European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
The FEBS Journal
|November 22, 2024
Summary
Enzymes can catalyze the same reaction with different structures, indicating functional convergence without evolutionary links. This study analyzes 34 cases, revealing diverse evolutionary paths for enzyme function.
Area of Science:
- Biochemistry
- Structural Biology
- Evolutionary Biology
Background:
- Enzymes catalyzing identical reactions often exhibit distinct structures.
- Functional convergence, where unrelated proteins evolve similar functions, is a key area in evolutionary biochemistry.
- The Mechanism and Catalytic Site Atlas (M-CSA) provides a rich resource for studying enzyme function and evolution.
Purpose of the Study:
- To identify and analyze cases of functional convergence in enzymes.
- To investigate the evolutionary independence of structurally diverse enzymes catalyzing the same reaction.
- To characterize the sequence, structural, and mechanistic features underlying enzyme functional convergence.
Main Methods:
- Utilized the M-CSA database to identify 34 cases of enzymes with identical Enzyme Commission numbers but different CATH folds.
- Compared sequence, structure, active site geometry, cofactor usage, and catalytic mechanisms of these enzyme pairs.
- Integrated literature data with computational resources (M-CSA, PDBe, PDBsum) and custom software for analysis.
Main Results:
- Identified 34 instances of functional convergence among enzymes with distinct folds.
- Demonstrated that these enzymes evolved independently to perform the same chemical catalysis.
- Observed multiple distinct patterns of convergent functional evolution.
Conclusions:
- Functional convergence in enzymes is a recurring phenomenon with diverse evolutionary strategies.
- Accurate description of enzyme convergence requires integrated analysis of sequence, structure, active site, and mechanism.
- This study highlights the power of integrating structural databases and computational tools for evolutionary insights.
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