CATH v4.4: major expansion of CATH by experimental and predicted structural data

IF 16.6 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Nucleic Acids Research Pub Date : 2024-11-20 DOI:10.1093/nar/gkae1087
Vaishali P Waman, Nicola Bordin, Andy Lau, Shaun Kandathil, Jude Wells, David Miller, Sameer Velankar, David T Jones, Ian Sillitoe, Christine Orengo
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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.
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CATH v4.4:通过实验和预测结构数据对 CATH 进行重大扩展
CATH(https://www.cathdb.info)是一个结构分类数据库,它为蛋白质数据库(PDB)和AlphaFold蛋白质结构数据库(AFDB)中的结构分配结构域,并添加多层生物信息,包括同源性和功能注释。本文介绍了自 2021 年以来 CATH 分类的发展情况。我们报告了通过对PDB结构域和来自结构域百科全书(TED)资源的预测结构域进行分类,CATH超家族的结构信息大幅扩展(180倍)。TED 提供了 AFDB 中的预测结构域信息。CATH v4.4 扩展了 PDB 中 64 844 个实验确定的结构域。我们还展示了从 TED 到 CATH 超家族的 9000 万个预测结构域的映射。新的 PDB 和 TED 数据将超家族的数量从 5841 个增加到 6573 个,折叠从 1349 个增加到 2078 个,结构从 41 个增加到 77 个。 TED 数据包括预测的结构,因此这些新的折叠和结构在实验证实之前仍然是假设的。CATH 还将结构域分类为超家族中的功能家族 (FunFams)。我们通过扫描 FunFam-HMM 与 UniProt release 2024_02 中的序列,更新了 FunFams 中的序列,使 FunFams 的覆盖率提高了 276%。TED 结构域的映射使含有结构信息的 FunFams 增加了 4 倍。
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来源期刊
Nucleic Acids Research
Nucleic Acids Research 生物-生化与分子生物学
CiteScore
27.10
自引率
4.70%
发文量
1057
审稿时长
2 months
期刊介绍: Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.
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