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Monte Carlo minimization with thermalization for global optimization of polypeptide conformations in cartesian
A Caflisch1, P Niederer, M Anliker
1Institute of Biomedical Engineering and Medical Informatics, Swiss Federal Institute of Technology, Zürich.
Proteins
|September 1, 1992
Summary
This study introduces a novel computational method combining Monte Carlo minimization with thermalization to find the global minimum energy conformation of polypeptide chains. Applied to methionine enkephalin, it identified a specific reverse turn structure, highlighting the influence of different energy functions.
Area of Science:
- Computational chemistry
- Molecular modeling
- Biophysics
Background:
- Determining the global minimum energy conformation of peptides is crucial for understanding their function.
- Existing methods can get trapped in local minima, hindering accurate conformational analysis.
Purpose of the Study:
- To present a new minimization procedure for global optimization of polypeptide chain conformational energy.
- To apply this method to methionine enkephalin and analyze its conformational landscape.
Main Methods:
- A novel minimization procedure combining Metropolis Monte Carlo minimization with a supplemental thermalization process.
- The thermalization process is triggered when structures are trapped in local energy minima.
- Application to the endogenous opioid pentapeptide methionine enkephalin using an in-house energy function.
Main Results:
- The method successfully identified an apparent global minimum energy conformation for methionine enkephalin.
- Five out of 13 starting conformations converged to the same global minimum: a type II' reverse turn (Gly-3-Phe-4).
- Comparison with ECEPP/2 force field revealed that similar minimum-energy conformations can arise from different energy functions.
Conclusions:
- The developed method is effective for global conformational energy optimization of peptides.
- The findings provide insights into the conformational preferences of methionine enkephalin.
- The study underscores the impact of energy functions on predicted peptide conformations.