Year: 2024
Type: article
Abstract: CATH (https://www.cathdb.info) is a structural classification database that assigns domains to the structures in the Protein Data Bank (PDB) and AlphaFold Protein Structure Database (AFDB) and adds layers of biological information, including homology and functional annotation. This article covers developments in the CATH classification since 2021. We report the significant expansion of structural information (180-fold) for CATH superfamilies through classification of PDB domains and predicted domain structures from the Encyclopedia of Domains (TED) resource. TED provides information on predicted domains in AFDB. CATH v4.4 represents an expansion of ∼64 844 experimentally determined domain structures from PDB. We also present a mapping of ∼90 million predicted domains from TED to CATH superfamilies. New PDB and TED data increases the number of superfamilies from 5841 to 6573, folds from 1349 to 2078 and architectures from 41 to 77. TED data comprises predicted structures, so these new folds and architectures remain hypothetical until experimentally confirmed. CATH also classifies domains into functional families (FunFams) within a superfamily. We have updated sequences in FunFams by scanning FunFam-HMMs against UniProt release 2024_02, giving a 276% increase in FunFams coverage. The mapping of TED structural domains has resulted in a 4-fold increase in FunFams with structural information.
Source: Nucleic Acids Research
DOI: 10.1093/nar/gkae1087
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $4,192
Awards: 3D-FunSites - a virtual encyclopaedia of protein functional sites for assessing variant impacts and drug repurposing, DTP Bid Led by University College London, G4731858957, G562141231, The HDRUK/Turing Wellcome PhD Programme in Health Data Science, G6688365311, Accelerating and enhancing the PSIPRED Workbench with deep learning, Transforming the Structural Landscape of CATH to Aid Variant Analyses in Human and Agricultural Organisms and their Pathogens, Exploiting Differentiable Programming Models For Protein Structure Prediction And Modelling, G8964389847
OpenAlex ID: W4404531739
