This article is part of the supplement: Selected articles from ISCB-Asia 2012
New enumeration algorithm for protein structure comparison and classification
1 Molecular Bioscience Graduate Program, Arkansas State University, Arkansas, USA
2 Bioinformatics Graduate Program, University of Arkansas at Little Rock, Arkansas, USA
3 School of Computing, DePaul University, Illinois, USA
4 Department of Computer Science, Lafayette College, Pennsylvania, USA
5 Department of Computer Science, Arkansas State University, Arkansas, USA
BMC Genomics 2013, 14(Suppl 2):S1 doi:10.1186/1471-2164-14-S2-S1Published: 15 February 2013
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.
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, efficient enumeration-based Protein structure Comparison) 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(1.47rnn2) 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.
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/ webcite.