NEW CONFORMATIONAL SEARCH METHOD USING GENETIC ALGORITHM AND KNOT THEORY FOR PROTEINS

被引:0
|
作者
Sakae, Y. [1 ]
Hiroyasu, T. [2 ]
Miki, M. [3 ]
Okamoto, Y. [1 ,4 ]
机构
[1] Nagoya Univ, Dept Phys, Nagoya, Aichi 4648602, Japan
[2] Doshisha Univ, Dept Biomed Informat, Kyoto 6100394, Japan
[3] Doshisha Univ, Dept Intelligent Informat Engn & Sci, Kyoto 6100394, Japan
[4] Nagoya Univ, Struct Biol Res Ctr, Nagoya, Aichi 4648602, Japan
关键词
Molecular Simulation; Simulated Annealing; Protein Folding; Genetic Algorithm; Knot Theory; CRYSTALLOGRAPHIC REFINEMENT; TERTIARY STRUCTURES; MOLECULAR-DYNAMICS; MODEL; OPTIMIZATION; PREDICTION; PEPTIDE;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
We have proposed a parallel simulated annealing using genetic crossover as one of powerful conformational search methods, in order to find the global minimum energy structures for protein systems. The simulated annealing using genetic crossover method, which incorporates the attractive features of the simulated annealing and the genetic algorithm, is useful for finding a minimum potential energy conformation of protein systems. However, when we perform simulations by using this method, we often find obviously unnatural stable conformations, which have "knots" of a string of an amino-acid sequence. Therefore, we combined knot theory with our simulated annealing using genetic crossover method in order to avoid the knot conformations from the conformational search space. We applied this improved method to protein G, which has 56 amino acids. As the result, we could perform the simulations, which avoid knot conformations.
引用
收藏
页码:217 / 228
页数:12
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