New conformational search method using genetic algorithm and knot theory for proteins.
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.
Department of Physics, Nagoya University, Nagoya, Aichi 464-8602, Japan. sakae@tb.phys.nagoya-u.ac.jp
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Sakae
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Hiroyasu
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Miki
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Okamoto
D000465:Algorithms; D001426:Bacterial Proteins / Q000737:chemistry; D019295:Computational Biology; D003198:Computer Simulation; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D013816:Thermodynamics
D001426:Bacterial Proteins; C034284:IgG Fc-binding protein, Streptococcus; D011506:Proteins