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A fully automatic evolutionary classification of protein folds: Dali Domain Dictionary version 3
Open accessAbstract
The Dali Domain Dictionary (http://www.ebi.ac.uk/dali/domain) is a numerical taxonomy of all known structures in the Protein Data Bank (PDB). The taxonomy is derived fully automatically from measurements of structural, functional and sequence similarities. Here, we report the extension of the classification to match the traditional four hierarchical levels corresponding to: (i) supersecondary structural motifs (attractors in fold space), (ii) the topology of globular domains (fold types), (iii) remote homologues (functional families) and (iv) homologues with sequence identity above 25% (sequence families). The computational definitions of attractors and functional families are new. In September 2000, the Dali classification contained 10 531 PDB entries comprising 17 101 chains, which were partitioned into five attractor regions, 1375 fold types, 2582 functional families and 3724 domain sequence families. Sequence families were further associated with 99 582 unique homologous sequences in the HSSP database, which increases the number of effectively known structures several-fold. The resulting database contains the description of protein domain architecture, the definition of structural neighbours around each known structure, the definition of structurally conserved cores and a comprehensive library of explicit multiple alignments of distantly related protein families.
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Cited by
Comparative protein structure modeling using MODELLER
Webb, B., & Sali, A. (2016) · Current Protocols in Protein Science · doi:10.1002/cpps.20 · Cited by 730
“The identi-fication of suitable templates is achieved by scanning structure databases, such as PDB (Berman et al., 2000), SCOP (Andreeva et al., 2004), DALI (Holm et al., 2006; also see Dietmann et al., 2001), and CATH (Pearl et al., 2005), with the target sequence as the query.”
MethodAravind, L., Anantharaman, V., & Koonin, E. V. (2002) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10064 · Cited by 153
Kang, H.-S., Nelson, M. L., Mackereth, C. D., Schärpf, M., Graves, B. J., & McIntosh, L. P. (2008) · Journal of Molecular Biology · doi:10.1016/j.jmb.2008.01.054 · Cited by 25
Improving diffusion-based protein backbone generation with global-geometry-aware latent encoding
(2025) · doi:10.1038/s42256-025-01059-x · Cited by 7
Metadata
- Authors
- Dietmann, S.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2001-01-01
- Volume
- 29
- Issue
- 1
- Pages
- 55-57
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2050956531
- Cited by
- 184
- References
- 0
- FWCI
- 6.08
- Type
- journal article
- Language
- en
- Open access
- bronze
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