School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430081, China.
Interdiscip Sci. 2010 Sep;2(3):256-62. doi: 10.1007/s12539-010-0033-x. Epub 2010 Jul 25.
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 offlattice 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.
蛋白质折叠问题是指通过最小化能量函数，从给定的氨基酸序列预测蛋白质的三级结构。当使用三维非格 AB 模型时，蛋白质折叠结构预测在计算上具有挑战性，并且已被证明是 NP 难问题。在本文中，局部调整遗传退火（LAGA）算法被用于搜索三维非格 AB 模型的蛋白质折叠结构的基态。该算法包括改进的交叉策略和改进的突变策略，其中还使用了局部调整策略来增强搜索能力。实验是使用斐波那契序列进行的。实验结果表明，与以前的方法相比，LAGA 算法具有更好的性能和准确性。
