Distance Constraint and Dihedral Angle Optimized Protein Structure Prediction Method
LI Ting1,LIU Jun1,ZHOU Xiao-gen2,ZHANG Gui-jun1
1(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310023,China)2(Department of Computational Medicine and Bioinformatics,University of Michigan,Ann Arbor,MI 48109,USA)
Abstract：Predicting the three-dimensional structure of a protein is of great significance for understanding its biological functions,research on disease pathogenesis,and drug development.In order to improve the accuracy of protein structure prediction,a protein structure prediction method(DCDA)based on distance constraint and dihedral angle optimization is proposed.First,the predicted distance distribution map between residues is screened,and then a conformation evaluation model based on the distance distribution between residues is constructed to guide conformation selection;then,based on the large-scale search of conformational space in fragment assembly,the use of dihedral-based the differential evolution sampling strategy enhances the sampling of the loop area with flexible structure,further improves the accuracy of the topological structure,and enhances the sampling ability of the near-natural state conformation.The prediction results of 15 test proteins show that DCDA can achieve high prediction accuracy,and it is an effective protein structure prediction method.
2022, Vol. 43 
