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PDBe-KB: collaboratively defining the biological context of structural data

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Authors

VARADI Mihaly ANYANGO Stephen ARMSTRONG David BERRISFORD John CHOUDHARY Preeti DESHPANDE Mandar NADZIRIN Nurul NAIR Sreenatha S. PRAVDA Lukas TANWEER Ahsan AL-LAZIKANI Bissan ANDREINI Claudia BARTON Geoffrey J. BEDNÁŘ David BERKA Karel BLUNDELL Tom BROCK Kelly P. MARIA CARAZO Jose DAMBORSKÝ Jiří DAVID Alessia DEY Sucharita DUNBRACK Roland RECIO Fernandez Juan FRATERNALI Franca GIBSON Toby HELMER-CITTERICH Manuela HOKSZA David HOPF Thomas JAKUBEC David KANNAN Natarajan KRIVAK Radoslav KUMAR Manjeet LEVY Emmanuel D. LONDON Nir MACIAS Jose Ramon SRIVATSAN Madhusudhan M. MARKS Debora S. MARTENS Lennart MCGOWAN Stuart A. MCGREIG Jake E. MODI Vivek PARRA Gonzalo R. PEPE Gerardo PIOVESAN Damiano PRILUSKY Jaime PUTIGNANO Valeria RADUSKY Leandro G. RAMASAMY Pathmanaban RAUSCH Atilio O. REUTER Nathalie RODRIGUEZ Luis A. ROLLINS Nathan J. ROSATO Antonio SERRANO Luis SINGH Gulzar SKODA Petr SORZANO Carlos Oscar S. ŠTOURAČ Jan SULKOWSKA Joanna I. SVOBODOVÁ Radka TICHSHENKO Natalia TOSATTO Silvio C. E. VRANKEN Wim WASS Mark N. XUE Dandan ZAIDMAN Daniel THORNTON Janet STERNBERG Michael ORENGO Christine VELANKAR Sameer

Year of publication 2022
Type Article in Periodical
Magazine / Source Nucleic acids research
MU Faculty or unit

Faculty of Science

Citation
Web https://academic.oup.com/nar/article/50/D1/D534/6424755?login=true
Doi http://dx.doi.org/10.1093/nar/gkab988
Keywords WEB SERVER; PROTEIN; PREDICT
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Description 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.
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