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Predicting protein stability changes upon mutation using database-derived potentials: solvent accessibility
1UCMB, Université Libre de Bruxelles, CP160/16 av. F. Roosevelt 50, Brussels, 1050, Belgium.
Journal of Molecular Biology
|September 23, 1997
Summary
This study evaluates database-derived potentials for predicting protein folding free energy changes due to mutations. Distance potentials best describe the protein core, while torsion potentials excel at the surface, improving prediction accuracy.
Area of Science:
- Biophysics
- Computational Biology
- Protein Science
Background:
- Protein stability is crucial for function.
- Understanding mutation effects on protein stability is key.
- Accurate prediction of folding free energy changes is essential.
Purpose of the Study:
- To estimate folding free energy changes upon mutation using database-derived potentials.
- To correlate computed changes with experimentally measured ones.
- To identify the best potentials for different residue burial states.
Main Methods:
- Utilized 238 mutations of buried and partially buried residues.
- Employed database-derived torsion potentials (local interactions) and distance potentials (non-local interactions).
- Correlated computed folding free energy changes with experimental data.
Main Results:
- A combination of distance and torsion potentials (0.4 weight) yielded a 0.80 correlation for totally buried residues.
- A combination of torsion and distance potentials (0.7 weight) achieved 0.82 correlation for partially buried residues.
- Torsion potentials individually reached 0.87 correlation for solvent-accessible residues.
Conclusions:
- Distance potentials, reflecting hydrophobic interactions, best stabilize the protein core.
- Torsion potentials best describe surface interactions and secondary structure formation.
- Local interactions, while not dominant in the core, significantly contribute to overall protein stability.