Protein structure comparison based on a measure of information discrepancy

Authors:
Zi-Kai Wu;Yong Wang;En-Min Feng;Jin-Cheng Zhao
Affiliations:
Department of Applied Mathematics, Dalian University of Technology, Dalian, P.R. China;Institude of Applied Mathematics, Academy of Mathematics and System Sciences, CAS, Beijing, P.R. China;Department of Applied Mathematics, Dalian University of Technology, Dalian, P.R. China;Institute of Bioinformatics and Molecular Design, Dalian University, Dalian, P.R. China
Venue:
TAMC'06 Proceedings of the Third international conference on Theory and Applications of Models of Computation
Year:
2006

Citing 4
Cited 0

The characterization of a measure of information discrepancy

Information Sciences—Applications: An International Journal
A measure of discrepancy of multiple sequences

Information Sciences: an International Journal
Measuring the similarity of protein structures by means of the universal similarity metric

Bioinformatics
Protein structure alignment by deterministic annealing

Bioinformatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Protein structure comparison is an important tool to explore and understand the different aspects of protein 3D structures. In this paper, a novel representation of protein structure (complete information set of Cα–Cα distances, CISD) is formulated at first. Then an FDOD score scheme is developed to measure the similarity between two representations. Numerical experiments of the new method are conducted in four different protein datasets and clustering analyses are given to verify the effectiveness of this new similarity measure. Furthermore, preliminary results of detecting homologous protein pairs of an existing non-redundant subset of CATH v2.5.1 based on the new similarity are given as a pilot study. All the results show that this new approach to measure the similarities between protein structures is simple to implement, computationally efficient and fast.