3D Protein Structure Prediction with BSA-TS Algorithm

Yan Xu, Changjun Zhou, Qiang Zhang, Bin Wang

Abstract: Three-dimensional protein spatial structure prediction with the amino acid sequence can be converted to a global optimization problem of a multi-variable and multimodal function. This article uses an improved hybrid optimization algorithm named BSA-TS algorithm which combines Backtracking Search Optimization Algorithm (BSA) with Tabu Search (TS) Algorithm to predict the structure of protein based on the three-dimensional AB off-lattice model. It combines the advantage of BSA which has a simple and efficient algorithm framework, less control parameters and less sensitivity to the initial value of the control parameters and the advantage of TS which has a strong ability for the global neighborhood search, and can better overcome the shortcomings of traditional algorithms which have slow convergence rate and are easy to fall into local optimum. At last we experiment in some Fibonacci sequences and real protein sequences which are widely used in protein spatial structure prediction, and the experimental results show that the hybrid algorithm has good performance and accuracy.