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Searching sequence space: two different approaches to dihydrofolate reductase catalysis
1Department of Biochemistry, Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996-0840, USA. lzh@utk.edu
Chembiochem : a European Journal of Chemical Biology
|April 7, 2005
Summary
Comparing two dihydrofolate reductases (DHFRs) with different structures reveals how protein scaffolds influence catalytic strategies. This highlights key factors in enzyme catalysis and evolution.
Area of Science:
- Biochemistry
- Enzyme kinetics
- Protein structure-function relationships
Background:
- Proteins can catalyze identical reactions using distinct structural frameworks.
- Dihydrofolate reductases (DHFRs) are crucial enzymes in folate metabolism.
- Comparing enzymes with varying evolutionary optimization provides insights into catalytic mechanisms.
Purpose of the Study:
- To compare the catalytic strategies of two DHFRs with significantly different structures: E. coli chromosomal DHFR (Ec DHFR) and R67 DHFR.
- To elucidate how the protein scaffold influences the catalytic efficiency and mechanism of DHFRs.
- To explore fundamental principles of enzyme catalysis and evolution using DHFR as a model system.
Main Methods:
- Comparative analysis of protein structures and catalytic mechanisms.
- Review of existing literature on Ec DHFR and R67 DHFR.
- Enzyme efficiency assessment based on reported kinetic data.
Main Results:
- Ec DHFR, a highly evolved enzyme, exhibits distinct structural and catalytic features compared to R67 DHFR.
- R67 DHFR, considered a 'primitive' enzyme, offers a contrasting model for understanding early enzyme evolution.
- Structural scaffolds significantly dictate the catalytic strategies employed by DHFR enzymes.
Conclusions:
- The scaffold of a protein is a primary determinant of its catalytic strategy.
- Comparative studies of enzymes with different evolutionary trajectories illuminate core principles of catalysis.
- Understanding DHFR structure-function relationships provides fundamental insights into enzyme evolution and optimization.