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用于非晶格蛋白质模型结构优化的退火轮廓蒙特卡罗算法

Annealing contour Monte Carlo algorithm for structure optimization in an off-lattice protein model.

作者信息

Liang Faming

机构信息

Department of Statistics, Texas A&M University, College Station, Texas 77843-3143, USA.

出版信息

J Chem Phys. 2004 Apr 8;120(14):6756-63. doi: 10.1063/1.1665529.

Abstract

We present a space annealing version for a contour Monte Carlo algorithm and show that it can be applied successfully to finding the ground states for an off-lattice protein model. The comparison shows that the algorithm has made a significant improvement over the pruned-enriched-Rosenbluth method and the Metropolis Monte Carlo method in finding the ground states for AB models. For all sequences, the algorithm has renewed the putative ground energy values in the two-dimensional AB model and set the putative ground energy values in the three-dimensional AB model.

摘要

我们提出了一种用于轮廓蒙特卡罗算法的空间退火版本,并表明它可以成功应用于寻找非晶格蛋白质模型的基态。比较结果表明,在寻找AB模型的基态方面,该算法相对于剪枝富集罗森布鲁斯方法和 metropolis 蒙特卡罗方法有了显著改进。对于所有序列,该算法更新了二维AB模型中的假定基态能量值,并设定了三维AB模型中的假定基态能量值。

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