Protein–protein interface prediction based on hexagon structure similarity. (August 2016)

• Record Type: Journal Article
• Authors: Guo, Fei; Ding, Yijie; Li, Shuai Cheng; Shen, Chao; Wang, Lusheng
• Is Part Of: Computational biology and chemistry. Volume 63(2016)
• Page Start: 83
• Page End: 88
• Publication Date: 2016-08
• Subjects: Protein–protein interface -- Hexagon structure -- Neighborhood information; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2016.02.008
• Languages: English
• ISSNs: 1476-9271

Abstract

Abstract: Studies on protein–protein interaction are important in proteome research. How to build more effective models based on sequence information, structure information and physicochemical characteristics, is the key technology in protein–protein interface prediction. In this paper, we study the protein–protein interface prediction problem. We propose a novel method for identifying residues on interfaces from an input protein with both sequence and 3D structure information, based on hexagon structure similarity. Experiments show that our method achieves better results than some state-of-the-art methods for identifying protein–protein interface. Comparing to existing methods, our approach improves F -measure value by at least 0.03. On a common dataset consisting of 41 complexes, our method has overall precision and recall values of 63% and 57%. On Benchmark v4.0, our method has overall precision and recall values of 55% and 56%. On CAPRI targets, our method has overall precision and recall values of 52% and 55%.