Real Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo

Real Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo

초록

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.

키워드

Protein folding; annealing contour Monte Carlo; simulated annealing; BLN model.
제목
Real Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo
제목 (타언어)
Real Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo
저자
전수영
발행일
2009
저널명
응용통계연구
권
22
호
3
페이지
627 ~ 634