New Conformational Search Method Using Genetic Algorithm and Knot Theory for ProteinsYoshitake Sakae1, Tomoyuki Hiroyasu2, Mitsunori Miki3, Yuko Okamoto1,4 1Department of Physics, Nagoya University, Nagoya, Aichi 464-8602, Japan; 2Department of Biomedical Information, Doshisha University, Kyotanabe, Kyoto 610-0394, Japan; 3Department of Intelligent Information Engineering and Sciences, Doshisha University, Kyotanabe, Kyoto 610-0394, Japan; 4Structural Biology Research Center, Nagoya University, Nagoya, Aichi 464-8602, Japan; Email: sakae@tb.phys.nagoya-u.ac.jp,tomo@is.doshisha.ac.jp, mmiki@mail.doshisha.ac.jp, okamoto@phys.nagoya-u.ac.jp Pacific Symposium on Biocomputing 16:217-228(2011) |
![]() |
AbstractWe 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. | |
[Full-Text PDF] [PSB Home Page] | |