Graph theoretic methods for the analysis of structural relationships in biological macromolecules

Subgraph isomorphism and maximum common subgraph isomorphism algorithms from graph theory provide an effective and 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. Methods available here are applicable to different types of biological macromolecules from carbohydrates to protein and nucleic acid structures.

Reference:
Peter J. Artymiuk, Ruth V. Spriggs and Willett, P. (2005) Graph theoretic methods for the analysis of structural relationships in biological macromolecules. Journal of the American Society for Information Science and Technology, 56, 518-528.
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The ASSAM program searches for 3D patterns of amino acid side chains in PDB formatted query structures.

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Primary References:
1. Spriggs RV, Artymiuk PJ, Willett P. (2003) Searching for patterns of amino acids in 3D protein structures. J Chem Inf Comput Sci. Mar-Apr;43(2):412-21.

2. Artymiuk PJ, Poirrette AR, Grindley HM, Rice DW, Willett P. (1994) A graph-theoretic approach to the identification of three-dimensional patterns of amino acid side-chains in protein structures. J Mol Biol. Oct 21;243(2):327-44.
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The NASSAM program searches for 3D motifs and patterns of bases in RNA (and RNA associated) PDB formatted query structures.

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Primary References
:
1. Firdaus-Raih et al.: Novel base triples in RNA structures revealed by graph theoretical searching methods. BMC Bioinformatics 2011 12(Suppl 13):S2.

2. Harrison, A-M, South, D.R., Willett, P., and Artymiuk, P.J. (2003) Representation, searching and discovery of patterns of bases in complex RNA structures. Journal of Computer-Aided Molecular Design, 17, 537-549.
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The SPRITE (3D Search for PRotein sITEs) server searches for protein sites and motifs in a query protein structure. The output is a list of potential functional sites.

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