New enumeration algorithm for protein structure comparison and classification

Background Protein structure comparison and classification is an effective method for exploring protein structure-function relations. This problem is computationally challenging. Many different computational approaches for protein structure comparison apply the secondary structure elements (SSEs) re...

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Bibliographic Details
Published inBMC genomics Vol. 14; no. Suppl 2; p. S1
Main Authors Ashby, Cody, Johnson, Daniel, Walker, Karl, Kanj, Iyad A, Xia, Ge, Huang, Xiuzhen
Format Journal Article
LanguageEnglish
Published London BioMed Central 2013
Springer Nature B.V
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ISSN1471-2164
1471-2164
DOI10.1186/1471-2164-14-S2-S1

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Summary:Background Protein structure comparison and classification is an effective method for exploring protein structure-function relations. This problem is computationally challenging. Many different computational approaches for protein structure comparison apply the secondary structure elements (SSEs) representation of protein structures. Results We study the complexity of the protein structure comparison problem based on a mixed-graph model with respect to different computational frameworks. We develop an effective approach for protein structure comparison based on a novel independent set enumeration algorithm. Our approach (named: ePC, e fficient e numeration-based P rotein structure C omparison) is tested for general purpose protein structure comparison as well as for specific protein examples. Compared with other graph-based approaches for protein structure comparison, the theoretical running-time O (1.47 rn n 2 ) of our approach ePC is significantly better, where n is the smaller number of SSEs of the two proteins, r is a parameter of small value. Conclusion Through the enumeration algorithm, our approach can identify different substructures from a list of high-scoring solutions of biological interest. Our approach is flexible to conduct protein structure comparison with the SSEs in sequential and non-sequential order as well. Supplementary data of additional testing and the source of ePC will be available at http://bioinformatics.astate.edu/ .
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ISSN:1471-2164
1471-2164
DOI:10.1186/1471-2164-14-S2-S1