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Title: | PDBe-KB: collaboratively defining the biological context of structural data |
Authors: | Varadi, Mihaly MADHUSUDHAN, M. S. SINGH, GULZAR et al. Dept. of Biology |
Keywords: | Web Server Protein Predict 2022-FEB-WEEK1 TOC-FEB-2022 2022 |
Issue Date: | Jan-2022 |
Publisher: | Oxford University Press |
Citation: | Nucleic Acids Research, 50(D1), D534–D542. |
Abstract: | The Protein Data Bank in Europe – Knowledge Base (PDBe-KB, https://pdbe-kb.org) is an open collaboration between world-leading specialist data resources contributing functional and biophysical annotations derived from or relevant to the Protein Data Bank (PDB). The goal of PDBe-KB is to place macromolecular structure data in their biological context by developing standardised data exchange formats and integrating functional annotations from the contributing partner resources into a knowledge graph that can provide valuable biological insights. Since we described PDBe-KB in 2019, there have been significant improvements in the variety of available annotation data sets and user functionality. Here, we provide an overview of the consortium, highlighting the addition of annotations such as predicted covalent binders, phosphorylation sites, effects of mutations on the protein structure and energetic local frustration. In addition, we describe a library of reusable web-based visualisation components and introduce new features such as a bulk download data service and a novel superposition service that generates clusters of superposed protein chains weekly for the whole PDB archive. |
URI: | https://doi.org/10.1093/nar/gkab988 http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/6557 |
ISSN: | 0305-1048 1362-4962 |
Appears in Collections: | JOURNAL ARTICLES |
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