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Bioinformatics Vol. 18 no. 2 2002
Pages 362-367
© 2002 Oxford University Press

Structure motif discovery and mining the PDB

Inge Jonassen 1,*, Ingvar Eidhammer 1, Darrell Conklin 2 and William R. Taylor 1,3

1 Department of Informatics, University of Bergen, HIB, N5020 Bergen, Norway
2 ZymoGenetics Inc., 1201 Eastlake Avenue East, Seattle, WA 98102, USA
3 Division of Mathematical Biology, National Institute of Medical Research, Mill Hill, London, UK

Received on March 2, 2001 ; revised on September 6, 2001 ; accepted on September 6, 2001

Motivation: Many of the most interesting functional and evolutionary relationships among proteins are so ancient that they cannot be reliably detected through sequence analysis and are apparent only through a comparison of the tertiary structures. The conserved features can often be described as structural motifs consisting of a few single residues or Secondary Structure (SS) elements. Confidence in such motifs is greatly boosted when they are found in more than a pair of proteins.

Results: We describe an algorithm for the automatic discovery of recurring patterns in protein structures. The patterns consist of individual residues having a defined order along the protein’s backbone that come close together in the structure and whose spatial conformations are similar. The residues in a pattern need not be close in the protein’s sequence. The work described in this paper builds on an earlier reported algorithm for motif discovery. This paper describes a significant improvement of the algorithm which makes it very efficient. The improved efficiency allows us to use it for doing unsupervised learning of patterns occurring in small subsets in a large set of structures, a non-redundant subset of the Protein Data Bank (PDB) database of all known protein structures.

Availability: The program is freely available to academia, requests can be sent to Inge.Jonassen{at}ii.uib.no.

Contact: Inge.Jonassen{at}ii.uib.no

* To whom correspondence should be addressed.


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