Authors:
Cody Ashby
1
;
Kun Wang
2
;
Carole L. Cramer
1
and
Xiuzhen Huang
1
Affiliations:
1
Arkansas State University, United States
;
2
University of Arkansas at Little Rock, United States
Keyword(s):
Protein structure-structure alignment, Color coding, Parameterized computation, Maximum common subgraph.
Related
Ontology
Subjects/Areas/Topics:
Algorithms and Software Tools
;
Bioinformatics
;
Biomedical Engineering
;
Model Design and Evaluation
;
Structural Bioinformatics
Abstract:
Motivated by the practical application of protein structure-structure alignment, we have studied the problem of
maximum common subgraph within the framework of parameterized complexity. We investigated the lower
bound for the exact algorithms of the problem. We proved it is unlikely that there is an algorithm of time
p(n,m) ∗ ko(m) for the problem, where p is a polynomial function, k is a parameter of map width, and m and n
are the numbers of vertices of the two graphs respectively. In consideration of the upper bound of p(n,m)∗km
based on the brute-force approach, our lower bound result is asymptotically tight. Although the algorithm with
the running time p(n,m) ∗ km could not be significantly improved from our lower bound result, it is still possible
to develop efficient algorithms for the practical application of the protein structure-structure alignment.
We developed an efficient algorithm integrating the color coding method and parameterized computation for
identifying the maxim
um common subgraph of two protein structure graphs. We have applied the algorithm
to protein structure-structure alignment and conducted experimental testing of more than 600 protein pairs.
Our parameterized approach shows improvement in structure alignment efficiency and will be very useful for
structure comparisons of proteins with large sizes.
(More)