3D Protein Structure Prediction with BSA-TS Algorithm
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 alg
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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. Keywords: Protein structure prediction BSA TS 3D AB off-lattice model
1 Introduction The study of protein structure helps us understand the function of proteins and to understand how they exercise their biological function, and understanding protein-protein interaction (or other molecules) is very important for biology, medicine and pharmacy [1]. In recent years, although the test methods for the determination of protein structures develop well, it’s still time-consuming, expensive, and not applied for some proteins difficult to crystallize. Therefore, we need to develop the theoretical analysis. With the development of computer technology, it has gradually become an important tool for processing large data of protein molecule. Theoretical Prediction of protein three-dimensional structure is mainly divided into the following three steps: Firstly, the mathematical model proposed should reflect the interaction among the amino acid residues; Secondly, we have to establish a simple calculated energy function which can also distinguish correctly between natural proteins and other proteins based on the thermodynamic hypothesis, Thirdly, we have to find the appropriate global optimization methods on the corresponding model to find the minimum of energy function. Owing to the efforts of researchers, we have had lots © Springer International Publishing Switzerland 2016 H. Fujita et al. (Eds.): IEA/AIE 2016, LNAI 9799, pp. 437–450, 2016. DOI: 10.1007/978-3-319-42007-3_38
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of achievements about the above steps. There are two widely used models named hydrophobic-polar (HP) model [2] and AB off-lattice model [3].The HP-lattice model uses two types of residues to present the amino acid chains which are hydrophobic (H) or non-polar residues and polar (P) or hydrophilic residues, and the residues on the vertices of stack cubic lattices are linked sequentially by unit-length chemical bonds [4–6]. This model is simple but it neglect
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