Graph theoretic methods for the analysis of structural relationships in biological macromolecules
Version of Record online: 19 JAN 2005
Copyright © 2005 Wiley Periodicals, Inc.
Journal of the American Society for Information Science and Technology
Special Issue: Bioinformatics
Volume 56, Issue 5, pages 518–528, March 2005
How to Cite
Artymiuk, P. J., Spriggs, R. V. and Willett, P. (2005), Graph theoretic methods for the analysis of structural relationships in biological macromolecules. J. Am. Soc. Inf. Sci., 56: 518–528. doi: 10.1002/asi.20140
- Issue online: 9 FEB 2005
- Version of Record online: 19 JAN 2005
- Manuscript Accepted: 22 APR 2004
Subgraph isomorphism and maximum common subgraph isomorphism algorithms from graph theory provide an effective and an efficient way of identifying structural relationships between biological macromolecules. They thus provide a natural complement to the pattern matching algorithms that are used in bioinformatics to identify sequence relationships. Examples are provided of the use of graph theory to analyze proteins for which three-dimensional crystallographic or NMR structures are available, focusing on the use of the Bron-Kerbosch clique detection algorithm to identify common folding motifs and of the Ullmann subgraph isomorphism algorithm to identify patterns of amino acid residues. Our methods are also applicable to other types of biological macromolecule, such as carbohydrate and nucleic acid structures.