蛋白质结构域边界网络流预测方法  

Protein Domain Boundary Network-flows Prediction Method

作　　者：余众泽 彭春祥 张贵军[1] YU Zhong-ze;PENG Chun-xiang;ZHANG Gui-jun(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China)

机构地区：[1]浙江工业大学信息工程学院,杭州310023

出　　处：《小型微型计算机系统》2023年第9期1892-1897,共6页Journal of Chinese Computer Systems

基　　金：国家重点研究开发计划项目(2019YFE0126100)资助;国家自然科学基金项目(62173304)资助;浙江省自然科学基金重点项目(LZ20F030002)资助.

摘　　要：结构域边界预测是蛋白质结构和功能研究的重要问题.针对目前大多数结构域边界预测方法精度低的局限性,提出一种基于网络流的蛋白质结构域边界预测算法GraphDom.该算法将蛋白质结构域边界预测问题转化为网络流分割问题,根据设计的边容量公式将预测的残基接触距离转换为蛋白质容量图,通过Ford-Fulkerson算法得到蛋白质剩余容量图,并使用深度优先算法和回溯算法获得强连接分量图并枚举所有可行的最小切割,最后基于结构域的一般特性设计域边界评估函数来评估划分的区域,并决定是否继续递归划分.在120个非冗余测试蛋白上与3种主流方法相比,显示了GraphDom的有效性.Domain boundary prediction is an important problem in the study of protein structure and function.Aiming at the limitation of low accuracy of most current domain boundary prediction methods,a network-flows based protein domain boundary prediction algorithm GraphDom is proposed.The algorithm converts the protein domain boundary prediction problem to a network flow segmentation problem.The predicted residue contact distances are converted into a protein capacity diagram according to the designed edge capacity transform formula,and then the protein residual capacity diagram is obtained by the Ford-Fulkerson algorithm.The depth-first algorithm and backtracking algorithm are used to obtain a strongly connected component diagram and enumerate all feasible minimum cuts according to the protein residual capacity diagram.Finally,the domain boundary evaluation function is designed based on the general properties of the domain to evaluate the divided partitions and then determine whether to continue the recursive division.The effectiveness of GraphDom is demonstrated on 120 non-redundant test proteins compared with 3 mainstream methods.

关 键 词：蛋白质结构域 结构域边界预测 网络流 接触距离 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]