Local Search Algorithm for Solving Protein Structure Prediction Problem
求解蛋白质结构预测问题的局部搜索算法

Protein structure prediction has proven to be one of the central problems in the field of computational biology. It is a feasible approach to predict theoretically the three-dimensional structure of proteins based only on amino acid sequence information. Using a new neighborhood structure and partly randomized off-trap strategy, a novel local search algorithm for protein structure prediction is proposed. Computational results demonstrate that our algorithm not only is more efficient than conventional genetic and Monte Carlo algorithms, but also find new configurations of lowest energy states missed in orevious papers for the sequence of length N=50