The CATH domain structure database: new protocols and classification levels give a more comprehensive resource for exploring evolution

By L. Greene, Tony E. Lewis, Sarah Addou, Alison L. Cuff, Timothy Dallman, Mark Dibley, Oliver Redfern, Frances M. G. Pearl, R. Nambudiry, A. Reid and 4 more. 2006

300 citations recorded by the source corpus.

We report the latest release (version 3.0) of the CATH protein domain database (). There has been a 20% increase in the number of structural domains classified in CATH, up to 86 151 domains. Release 3.0 comprises 1110 fold groups and 2147 homologous superfamilies. To cope with the increases in diverse structural homologues being determined by the structural genomics initiatives, more sensitive methods have been developed for identifying boundaries in multi-domain proteins and for recognising homologues. The CATH classification update is now being driven by an integrated pipeline that links these automated procedures with validation steps, that have been made easier by the provision of information rich web pages summarising comparison scores and relevant links to external sites for each domain being classified. An analysis of the population of domains in the CATH hierarchy and several domain characteristics are presented for version 3.0. We also report an update of the CATH Dictionary of homologous structures (CATH-DHS) which now contains multiple structural alignments, consensus information and functional annotations for 1459 well populated superfamilies in CATH. CATH is directly linked to the Gene3D database which is a projection of CATH structural data onto ∼2 million sequences in completed genomes and UniProt.

Subfields: Molecular Biology

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Citations in the corpus

DeepSF: deep convolutional neural network for mapping protein sequences to folds (2017, methodology): “Several fold classification databases such as SCOP (Murzin et al., 1995), CATH (Greene et al., 2007), FSSP (Holm and Sander, 1994), ECOD (Cheng et al., 2014) have been developed to summarize the structural relationship between VC The Author 2017.”
Protein annotation and modelling servers at University College London (2010, background): “The sequence alignments are now presented in a fully interactive form using JalView (11); and we also now include links which allow users to explore functional and structural data derived from both the CATH and Gene3D databases (12).”
Protein structure homology modeling using SWISS-MODEL workspace (2008, background): “Individual structural domains of multidomain proteins often correspond to units of distinct molecular functio”
PDBe: Protein Data Bank in Europe (2010, methodology): “The tab also shows the distribution of the most frequent CATH classes and architectures for the selected enzyme class as pie charts.”
Extending CATH: increasing coverage of the protein structure universe and linking structure with function (2010, background): “Indeed, there has been a gradual decrease in the number of new folds identified over the last decade (5).”
ProFET: Feature engineering captures high-level protein functions (2015, background): “This is best demonstrated by the limitation in classifying proteins by their 3D-folds (Greene et al. , 2007; Todd et al. , 2005).”
Understanding eukaryotic linear motifs and their role in cell signaling and regulation. (2008, unknown): “Many bioinformatics tools are also available for studies of globular domains, including SMART, Pfam, CDD, SCOP and CATH (6-10).”
The High-Throughput Protein Sample Production Platform of the Northeast Structural Genomics Consortium (2010, unknown): “CATH superfamily identification numbers (Greene et al., 2007) are”