基于K-mer扭转角偏好的蛋白质结构类型预测

蛋白质的序列、结构和功能多种多样。大量研究表明蛋白质的结构与其氨基酸序列的排序有关,并且局部的氨基酸序列环境对蛋白质的结构具有一定的影响。本文提出一种新的基于5-mer氨基酸扭转角统计偏好的蛋白质结构类型预测方法,该方法通过PDB数据库中5-mer中间氨基酸的扭转角统计偏好来进行结构类型的预测。新方法可以通过计算机仿真实现对新蛋白质序列结构类型的快速预测,并通过两组随机抽取的CATH数据验证了新方法的有效性。

Protein structural type prediction based on the torsion angle preference of K-mers

Proteins are varied with their sequences, structures, and functions. A large number of studies have shown that the structures of proteins are encoded by the amino acids arrangement of their sequences, and local sequence patterns may have impact on the structural types of proteins. In this paper, we propose a new protein structural classification method based on the torsion angle statistics preference of 5-mers, where the protein structural types are predicted by the statistical inclination of the torsion angles for the middle amino acids of 5-mers in the PDB database. The new method can be used to predict structural types for new protein sequences via computer simulations. Two randomly chosen CATH datasets were used to demonstrate the efficiency of the new method.