A new prediction protein structure method based on Genetic Algorithm and Coarse-grained protein model

被引:0
|
作者
Wang Cai-Yun [1 ]
Zhu Hao-Dong [2 ]
Cai Le-Cai [1 ]
机构
[1] Sichuan Univ Sci & Engn, Dept Elect & Technol, Zigong Sichuan 643000, Peoples R China
[2] Chinese Acad Sci, Chengdu Inst Comp Applicat, Chengdu 610041, Peoples R China
关键词
Genetic Algorithm; Coarse-grained protein model; structure prediction; De novo prediction; MOLECULAR-DYNAMICS; TASSER; OPTIMIZATION; SIMULATIONS; ROSETTA; CHAINS;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
De novo prediction of protein structures, structures prediction from amino acid sequences which are not similar to those of hitherto resolved structures, has been one of the major challenges in bioinformatics. A new prediction protein structure method based on Genetic Algorithm and Coarse-grained protein model is presented. Genetic Algorithm is a high performance optimization method and can effectively assemble a separate sequence, and Coarse-grained protein model have consistently assembled fragments are dynamically searched by Langevin molecular dynamics of conformational change. This new method combines the advantages of Genetic Algorithm and Coarse-grained protein model, which will improve the accuracy of protein structure prediction.
引用
收藏
页码:1419 / +
页数:3
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