Effective 3D Protein Structure Prediction with Local Adjustment Genetic-annealing Algorithm

被引:4
|
作者
Zhang, Xiao-Long [1 ]
Lin, Xiao-Li [2 ]
机构
[1] Wuhan Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430081, Peoples R China
[2] Wuhan Univ Sci & Technol, City Coll, Informat & Engn Dept, Wuhan 430083, Peoples R China
基金
中国国家自然科学基金;
关键词
protein folding structure; off-lattice AB model; LAGA; local adjustment; mutation; crossover; TOY MODEL; OPTIMIZATION;
D O I
10.1007/s12539-010-0033-x
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The protein folding problem consists of predicting protein tertiary structure from a given amino acid sequence by minimizing the energy function. The protein folding structure prediction is computationally challenging and has been shown to be NP-hard problem when the 3D off-lattice AB model is employed. In this paper, the local adjustment genetic-annealing (LAGA) algorithm was used to search the ground state of 3D off-lattice AB model for protein folding structure. The algorithm included an improved crossover strategy and an improved mutation strategy, where a local adjustment strategy was also used to enhance the searching ability. The experiments were carried out with the Fibonacci sequences. The experimental results demonstrate that the LAGA algorithm appears to have better performance and accuracy compared to the previous methods.
引用
收藏
页码:256 / 262
页数:7
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