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PMID: 9191068 Published · ppublish English Comparative Study Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.

Protein folding simulations with genetic algorithms and a detailed molecular description.

Journal of molecular biology ·Vol. 269 ·No. 2 ·1997-06-06 ·Pages 240-59

Pedersen JT, Moult J

Abstract

We have explored the application of genetic algorithms (GA) to the determination of protein structure from sequence, using a full atom representation. A free energy function with point charge electrostatics and an area based solvation model is used. The method is found to be superior to previously investigated Monte Carlo algorithms. For selected fragments, up to 14 residues long, the lowest free energy structures produced by the GA are similar in conformation to the corresponding experimental structures in most cases. There are three main conclusions from these results. First, the genetic algorithm is an effective method for searching amongst the compact conformations of a polypeptide chain. Second, the free energy function is generally able to select native-like conformations. However, some deficiencies are identified, and further development is proposed. Third, the selection of native-like conformations for some protein fragments establishes that in these cases the conformation observed in the full protein structure is largely context independent. The implications for the nature of protein folding pathways are discussed.

MeSH Terms
Algorithms Aprotinin/chemistry Bacterial Proteins Computer Simulation Models, Chemical Models, Molecular Molecular Sequence Data Peptide Fragments/chemistry Protein Conformation Protein Folding Reproducibility of Results Ribonucleases/chemistry Thermodynamics
Chemicals
Bacterial Proteins Peptide Fragments Aprotinin Ribonucleases Bacillus amyloliquefaciens ribonuclease
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Pedersen J T
Center for Advanced Research in Biotechnology, University of Maryland Biotechnology Institute, Rockville, MD 20850, USA.
Moult J
Article Info
Journal
Journal of molecular biology
Abbr.
J Mol Biol
ISSN
0022-2836
Published
1997-06-06
Pages
240-59
Language
English
Region
England
NLM ID
2985088R
Subset
IM
Grants
NIGMS NIH HHS · GM40134 · United States
Databases
PDB
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