Literature DB >> 9191068

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

J T Pedersen1, J Moult.   

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.

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Year:  1997        PMID: 9191068     DOI: 10.1006/jmbi.1997.1010

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  13 in total

1.  Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction.

Authors:  Hongyi Zhou; Yaoqi Zhou
Journal:  Protein Sci       Date:  2002-11       Impact factor: 6.725

2.  A novel approach to decoy set generation: designing a physical energy function having local minima with native structure characteristics.

Authors:  Chen Keasar; Michael Levitt
Journal:  J Mol Biol       Date:  2003-05-23       Impact factor: 5.469

3.  Comparative protein structure modeling by iterative alignment, model building and model assessment.

Authors:  Bino John; Andrej Sali
Journal:  Nucleic Acids Res       Date:  2003-07-15       Impact factor: 16.971

4.  Contact order and ab initio protein structure prediction.

Authors:  Richard Bonneau; Ingo Ruczinski; Jerry Tsai; David Baker
Journal:  Protein Sci       Date:  2002-08       Impact factor: 6.725

5.  An evolutionary strategy for all-atom folding of the 60-amino-acid bacterial ribosomal protein l20.

Authors:  A Schug; W Wenzel
Journal:  Biophys J       Date:  2006-03-24       Impact factor: 4.033

6.  A multi-objective evolutionary approach to the protein structure prediction problem.

Authors:  Vincenzo Cutello; Giuseppe Narzisi; Giuseppe Nicosia
Journal:  J R Soc Interface       Date:  2006-02-22       Impact factor: 4.118

7.  A free-rotating and self-avoiding chain model for deriving statistical potentials based on protein structures.

Authors:  Ji Cheng; Jianfeng Pei; Luhua Lai
Journal:  Biophys J       Date:  2007-03-09       Impact factor: 4.033

8.  Low-resolution structures of proteins in solution retrieved from X-ray scattering with a genetic algorithm.

Authors:  P Chacón; F Morán; J F Díaz; E Pantos; J M Andreu
Journal:  Biophys J       Date:  1998-06       Impact factor: 4.033

9.  Application of evolutionary algorithm methods to polypeptide folding: comparison with experimental results for unsolvated Ac-(Ala-Gly-Gly)5-LysH+.

Authors:  Martin Damsbo; Brian S Kinnear; Matthew R Hartings; Peder T Ruhoff; Martin F Jarrold; Mark A Ratner
Journal:  Proc Natl Acad Sci U S A       Date:  2004-04-30       Impact factor: 11.205

10.  Protein structure prediction by all-atom free-energy refinement.

Authors:  Abhinav Verma; Wolfgang Wenzel
Journal:  BMC Struct Biol       Date:  2007-03-19
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