Protein structural domains: Analysis of the 3Dee domains database

Abstract

The 3Dee database of domain definitions was developed as a comprehensive collection of domain definitions for all three-dimensional structures in the Protein Data Bank (PDB). The database includes definitions for complex, multiple-segment and multiple-chain domains as well as simple sequential domains, organized in a structural hierarchy. Two different snapshots of the 3Dee database were analyzed at September 1996 and November 1999. For the November 1999 release, 7,995 PDB entries contained 13,767 protein chains and gave rise to 18,896 domains. The domain sequences clustered into 1,715 domain sequence families, which were further clustered into a conservative 1,199 domain structure families (families with similar folds). The proportion of different domain structure families per domain sequence family increases from 84% for domains 1-100 residues long to 100% for domains greater than 600 residues. This is in keeping with the idea that longer chains will have more alternative folds available to them. Of the representative domains from the domain sequence families, 49% are in the range of 51-150 residues, whereas 64% of the representative chains over 200 residues have more than 1 domain. Of the representative chains, 8.5% are part of multichain domains. The largest multichain domain in the database has 14 chains and 1,400 residues, whereas the largest single-chain domain has 907 residues. The largest number of domains found in a protein is 13. The analysis shows that over the history of the PDB, new domain folds have been discovered at a slower rate than by random selection of all known folds. Between 1992 and 1997, a constant 1 in 11 new domains deposited in the PDB has shown no sequence similarity to a previously known domain sequence family, and only 1 in 15 new domain structures has had a fold that has not been seen previously. A comparison of the September 1996 release of 3Dee to the Structural Classification of Proteins (SCOP) showed that the domain definitions agreed for 80% of the representative protein chains. However, 3Dee provided explicit domain boundaries for more proteins. 3Dee is accessible on the World Wide Web at http://barton.ebi.ac.uk/servers/3Dee.html.

Protein contacts, inter-residue interactions and side-chain modelling

“…Hence, methods for phylogenetic analyses and protein modelling usually perform better for single domains [58]. Automatic domain parsing generally makes the assumption that interdomain interaction (under a correct domain assignment) is weaker than the intradomain interaction (PUU [59], DOMAK [60] and 3Dee [61,62], DETECTIVE [63], DALI [64], STRUDL [65], DomainParser [66,67], Protein Domain Parser [68] and DDOMAIN [69]). These approaches maximize the number of contacts within a domain.…”

OXBench: A benchmark for evaluation of protein multiple sequence alignment accuracy

“…Reference proteins for alignment were drawn from the 3Dee database of structural domains [23,24]. 3Dee contains domain definitions for proteins of experimentally determined three-dimensional structure in the Protein Data Bank (PDB) up to July 1998.…”

“…With so few alignments in this range it is difficult to see significant differences between methods, though general trends are apparent. The deficit in low percentage identity alignments is partly due to the automatic sequence/structure clustering used to construct the 3Dee domains database [23,24] and the need to avoid incorrect clusters. In the 3Dee structural hierarchy, the domain sequences are first clustered on sequence similarity, then representatives taken and clustered by structure comparison [23,24].…”

“…The benchmark data set is made up of domain families obtained from the 3Dee database of protein structural domains [23,24]. After filtering these families by different criteria, reference structural alignments were determined by the STAMP algorithm [25].…”

Analysis of protein contacts into Protein Units

“…Methods for phylogenetic analyses or protein modeling usually perform best for single domains [29]. The commonly used principle for automatic domain parsing is that interdomain interaction under a correct domain assignment is weaker than the intradomain interaction (PUU [30], DOMAK [31], 3Dee [32,33], DETECTIVE [34], DALI [35], STRUDL [36], DomainParser [37,38], Protein Domain Parser [39] and DDOMAIN [40]). Innovative approaches have been used in this context, e.g., graph theory [41] and Normal Mode Analysis approach [42].…”