The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Real Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo

  • Cheon, Soo-Young (KU Industry-Academy Cooperation Group Team of Economics and Statistics, Korea University)
  • Published : 2009.06.30
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Abstract

Recently, the general contour Monte Carlo has been proposed by Liang (2004) as a space annealing version(ACMC) for optimization problems. The algorithm can be applied successfully to determine the ground configurations for the prediction of protein folding. In this approach, we use the distances between the consecutive $C_{\alpha}$ atoms along the peptide chain and the mapping sequences between the 20-letter amino acids and a coarse-grained three-letter code. The algorithm was tested on the real proteins. The comparison showed that the algorithm made a significant improvement over the simulated annealing(SA) and the Metropolis Monte Carlo method in determining the ground configurations.

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References

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