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.
CITATION STYLE
Vinayagam, A., Shi, J., Pugalenthi, G., Meenakshi, B., Blundell, T. L., & Sowdhamini, R. (2003). DDBASE2.0: Updated domain database with improved identification of structural domains. Bioinformatics, 19(14), 1760–1764. https://doi.org/10.1093/bioinformatics/btg233
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