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On evolutionary conservation of thermodynamic coupling in proteins
Anthony A Fodor1, Richard W Aldrich
1Department of Molecular and Cellular Physiology, and Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, California 94305-5345, USA.
The Journal of Biological Chemistry
|March 17, 2004
Summary
Correlated mutation algorithms can identify physically close protein residues that are thermodynamically coupled. However, evidence does not support the idea that this coupling is limited to evolutionarily constrained positions.
Area of Science:
- Protein science
- Biophysics
- Computational biology
Background:
- Thermodynamic coupling in proteins is complex, hindering function understanding and engineering.
- Correlated mutation analysis suggests a simplified approach by identifying key residues in conserved energetic pathways.
Purpose of the Study:
- To test the hypothesis that correlated mutation algorithms can identify thermodynamically coupled residues in proteins.
- To evaluate if thermodynamic coupling is restricted to evolutionarily constrained positions.
Main Methods:
- Applied correlated mutation algorithms to various proteins.
- Validated predictions against experimental data from double mutant cycle analyses.
Main Results:
- Correlated mutation algorithms successfully identified residue pairs that are physically proximate.
- Physically close residue pairs showed a tendency towards thermodynamic coupling.
- Limited evidence was found to support the restriction of thermodynamic coupling to evolutionarily constrained sites.
Conclusions:
- Correlated mutation analysis is a viable method for identifying physically proximate and thermodynamically coupled residues.
- The hypothesis that thermodynamic coupling is exclusively confined to evolutionarily constrained positions is not supported by this study.