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Protein Folding Simulation by Two-Stage Optimization

  • A. Dayem Ullah
  • L. Kapsokalivas
  • M. Mann
  • K. Steinhöfel
Part of the Communications in Computer and Information Science book series (CCIS, volume 51)

Abstract

This paper proposes a two-stage optimization approach for protein folding simulation in the FCC lattice, inspired from the phenomenon of hydrophobic collapse. Given a protein sequence, the first stage of the approach produces compact protein structures with the maximal number of contacts among hydrophobic monomers, using the CPSP tools for optimal structure prediction in the HP model. The second stage uses those compact structures as starting points to further optimize the protein structure for the input sequence by employing simulated annealing local search and a 20 amino acid pairwise interactions energy function. Experiment results with PDB sequences show that compact structures produced by the CPSP tools are up to two orders of magnitude better, in terms of the pairwise energy function, than randomly generated ones. Also, initializing simulated annealing with these compact structures, yields better structures in fewer iterations than initializing with random structures. Hence, the proposed two-stage optimization outperforms a local search procedure based on simulated annealing alone.

Keywords

Local Search Simulated Annealing Constraint Programming Local Search Method Local Search Procedure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • A. Dayem Ullah
    • 1
  • L. Kapsokalivas
    • 1
  • M. Mann
    • 2
  • K. Steinhöfel
    • 1
  1. 1.Department of Computer ScienceKing’s College LondonLondonUK
  2. 2.Bioinformatics GroupUniversity of FreiburgFreiburgGermany

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