DDBASE2.0: Updated domain database with improved identification of structural domains

A. Vinayagam, J. Shi, G. Pugalenthi, B. Meenakshi, T. L. Blundell, R. Sowdhamini*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Motivation: Although many methods are available for the identification of structural domains from protein three-dimensional structures, accurate definition of protein domains and the curation of such data for a large number of proteins are often possible only after manual intervention. The availability of domain definitions for protein structural entries is useful for the sequence analysis of aligned domains, structure comparison, fold recognition procedures and understanding protein folding, domain stability and flexibility. Results: We have improved our method of domain identification starting from the concept of clustering secondary structural elements, but with an intention of reducing the number of discontinuous segments in identified domains. The results of our modified and automatic approach have been compared with the domain definitions from other databases. On a test data set of 55 proteins, this method acquires high agreement (88%) in the number of domains with the crystallographers' definition and resources such as SCOP, CATH, DALI, 3Dee and PDP databases. This method also obtains 98% overlap score with the other resources in the definition of domain boundaries of the 55 proteins. We have examined the domain arrangements of 4592 non-redundant protein chains using the improved method to include 5409 domains leading to an update of the structural domain database.

Original languageEnglish (US)
Pages (from-to)1760-1764
Number of pages5
Issue number14
StatePublished - Sep 22 2003
Externally publishedYes

Bibliographical note

Funding Information:
R.S. is a recipient of Senior Research Fellowship awarded by the Wellcome Trust, UK. A.V. and, G.P. are supported by the Wellcome Trust. We also thank NCBS (TIFR) for infrastructural support.

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics


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