Unified access to up-to-date residue-level annotations from UniProtKB and other biological databases for PDB data.

Unified access to up-to-date residue-level annotations from UniProtKB and other biological databases for PDB data.
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DOI:
10.1038/s41597-023-02101-6
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发表时间:
2023-04-12
期刊:
影响因子:
9.8
通讯作者:
Velankar, Sameer
Velankar, Sameer
中科院分区:
综合性期刊2区
文献类型:
--
作者:
Choudhary, Preeti;Anyango, Stephen;Berrisford, John;Tolchard, James;Varadi, Mihaly;Velankar, Sameer

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借助“结构与功能、分类学及序列整合”(SIFTS)资源,超过6.1万种蛋白质的氨基酸序列(UniProtKB)与其三维结构(PDB)实现了最新对应。SIFTS整合了来自许多其他生物资源的残基层面注释。SIFTS数据有多种格式,如XML、CSV和TSV格式,也可通过PDBe REST API获取,但在PDB数据库中,它始终与结构数据(PDBx/mmCIF文件)分开维护。在此,我们对wwPDB PDBx/mmCIF数据字典进行了扩展,增加了额外类别以纳入SIFTS数据,并将UniProtKB、Pfam、SCOP2和CATH的残基层面注释直接添加到PDB数据库的PDBx/mmCIF文件中。有了整合后的UniProtKB注释,这些文件现在能对不同PDB条目里的残基进行一致编号,便于对结构模型进行比较。扩展后的字典在不改变PDB核心信息的情况下,生成了更一致、标准化的元数据描述。这一进展实现了残基层面的最新交叉引用信息,从而提升了数据的互操作性,有助于改进数据分析与可视化。
More than 61,000 proteins have up-to-date correspondence between their amino acid sequence (UniProtKB) and their 3D structures (PDB), enabled by the Structure Integration with Function, Taxonomy and Sequences (SIFTS) resource. SIFTS incorporates residue-level annotations from many other biological resources. SIFTS data is available in various formats like XML, CSV and TSV format or also accessible via the PDBe REST API but always maintained separately from the structure data (PDBx/mmCIF file) in the PDB archive. Here, we extended the wwPDB PDBx/mmCIF data dictionary with additional categories to accommodate SIFTS data and added the UniProtKB, Pfam, SCOP2, and CATH residue-level annotations directly into the PDBx/mmCIF files from the PDB archive. With the integrated UniProtKB annotations, these files now provide consistent numbering of residues in different PDB entries allowing easy comparison of structure models. The extended dictionary yields a more consistent, standardised metadata description without altering the core PDB information. This development enables up-to-date cross-reference information at the residue level resulting in better data interoperability, supporting improved data analysis and visualisation.
DOI: 10.1093/nar/gkaa977
发表时间: 2021-01-08
影响因子: 14.9
作者:
Blum M;Chang HY;Chuguransky S;Grego T;Kandasaamy S;Mitchell A;Nuka G;Paysan-Lafosse T;Qureshi M;Raj S;Richardson L;Salazar GA;Williams L;Bork P;Bridge A;Gough J;Haft DH;Letunic I;Marchler-Bauer A;Mi H;Natale DA;Necci M;Orengo CA;Pandurangan AP;Rivoire C;Sigrist CJA;Sillitoe I;Thanki N;Thomas PD;Tosatto SCE;Wu CH;Bateman A;Finn RD
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DOI: 10.1093/nar/gkaa1113
发表时间: 2021-01-08
影响因子: 14.9
作者:
Gene Ontology Consortium
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DOI: 10.1093/nar/gky949
发表时间: 2019-01-08
影响因子: 14.9
作者:
wwPDB consortium
通讯作者: wwPDB consortium
DOI: 10.1093/nar/gkx1095
发表时间: 2018-01-04
影响因子: 14.9
作者:
NCBI Resource Coordinators
通讯作者: NCBI Resource Coordinators
DOI: 10.1002/prot.21510
发表时间: 2008-02-01
影响因子: 2.9
作者:
Brylinski, Michal;Skolnick, Jeffrey
通讯作者: Skolnick, Jeffrey