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STOCHASTICOPTIMIZATION METHODS FOR PROTEIN FOLDING

  • ALEXANDER SCHUG
  • THOMAS HERGES
  • ABHINAV VERMA
  • WOLFGANG WENZEL
Conference paper
Part of the Progress in Theoretical Chemistry and Physics book series (PTCP, volume 15)

Abstract

We recently developed an all-atom free energy force field (PFF01) for protein structure prediction with stochastic optimization methods. We demonstrated that PFF01 correctly predicts the native conformation of several proteins as the global optimum of the free energy surface. Here we review recent folding studies, which permitted the reproducible all-atom folding of the 20 amino-acid trp-cage protein, the 40-amino acid three-helix HIV accessory protein and the sixty amino acid bacterial ribosomal protein L20 with a variety of stochastic optimization methods. These results demonstrate that all-atom protein folding can be achieved with present day computational resources for proteins of moderate size.

Keywords

Potential Energy Surface Free Energy Surface Native Conformation Protein Structure Prediction Secondary Structure Content 
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 2006

Authors and Affiliations

  • ALEXANDER SCHUG
    • 1
  • THOMAS HERGES
    • 1
  • ABHINAV VERMA
    • 1
  • WOLFGANG WENZEL
    • 1
  1. 1.Institut für NanotechnologieForschungszentrum KarlsruheKarlsruheGermany

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