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

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PDBe-KB consortium, Varadi, Mihaly, Anyango, Stephen, Armstrong, David, Berrisford, John, Choudhary, Preeti, Deshpande, Mandar, Nadzirin, Nurul +64 more·2022·Nucleic Acids Research
DOI 10.1093/nar/gkab988PMC PMC8728252
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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.

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  • The impact of predicted structures is enhanced by their seamless integration into several core data resources, including PDBe-KB, UniProt, Ensembl, InterPro, Genecards and MobiDB.

    “The impact of the predicted structures is further enhanced by their seamless integration into several core data resources, including PDBe-KB (17), UniProt (6), Ensembl (16), InterPro (15), Genecards (24) and MobiDB (25), among others.”

    From AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences (2024) · cites this paper as [17]

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  1. [1]Lee D., Redfern O., Orengo C. Predicting protein function from sequence and structure. Nat. Rev. Mol. Cell Biol. 2007; 8: 995– 1005. 18037900
  2. [2]Waman V.P., Sen N., Varadi M., Daina A., Wodak S.J., Zoete V., Velankar S., Orengo C. The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies. Brief. Bioinform. 2021; 22: 742– 768. 33348379 PMC7799268
  3. [3]Knott B.C., Erickson E., Allen M.D., Gado J.E., Graham R., Kearns F.L., Pardo I., Topuzlu E., Anderson J.J., Austin H.P. et al. Characterization and engineering of a two-enzyme system for plastics depolymerization. Proc. Natl. Acad. Sci. U.S.A. 2020; 117: 25476– 25485. 32989159 PMC7568301
  4. [4]Batool M., Ahmad B., Choi S. A structure-based drug discovery paradigm. Int. J. Mol. Sci. 2019; 20: 2783. PMC6601033 31174387
  5. [5]Marques S.M., Planas-Iglesias J., Damborsky J. Web-based tools for computational enzyme design. Curr. Opin. Struct. Biol. 2021; 69: 19– 34. 33667757
  6. [6]wwPDB consortium Burley S.K., Berman H.M., Bhikadiya C., Bi C., Chen L., Costanzo L.D., Christie C., Duarte J.M., Dutta S. et al. Protein Data Bank: the single global archive for 3D macromolecular structure data. Nucleic Acids Res. 2019; 47: D520– D528. 30357364 PMC6324056
  7. [7]Armstrong D.R., Berrisford J.M., Conroy M.J., Gutmanas A., Anyango S., Choudhary P., Clark A.R., Dana J.M., Deshpande M., Dunlop R. et al. PDBe: improved findability of macromolecular structure data in the PDB. Nucleic Acids Res. 2019; 48: D335– D343. PMC7145656 31691821
  8. [8]Masrati G., Landau M., Ben-Tal N., Lupas A., Kosloff M., Kosinski J. Integrative structural biology in the era of accurate structure prediction. J. Mol. Biol. 2021; 433: 167127. 34224746
  9. [9]Consortium The UniProt Bateman A., Martin M.-J., Orchard S., Magrane M., Agivetova R., Ahmad S., Alpi E., Bowler-Barnett E.H., Britto R. et al. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 2021; 49: D480– D489. 33237286 PMC7778908
  10. [10]Velankar S., Burley S.K., Kurisu G., Hoch J.C., Markley J.L. Owens R.J. The Protein Data Bank Archive. Structural Proteomics, Methods in Molecular Biology. 2021; 2305: New York, NY Springer US 3– 21. 33950382
  11. [11]Dana J.M., Gutmanas A., Tyagi N., Qi G., O’Donovan C., Martin M., Velankar S. SIFTS: updated structure integration with function, taxonomy and sequences resource allows 40-fold increase in coverage of structure-based annotations for proteins. Nucleic Acids Res. 2019; 47: D482– D489. 30445541 PMC6324003
  12. [12]Baek M., DiMaio F., Anishchenko I., Dauparas J., Ovchinnikov S., Lee G.R., Wang J., Cong Q., Kinch L.N., Schaeffer R.D. et al. Accurate prediction of protein structures and interactions using a three-track neural network. Science. 2021; 373: 871– 876. 34282049 PMC7612213
  13. [15]consortium PDBe-KB, Varadi M., Berrisford J., Deshpande M., Nair S.S., Gutmanas A., Armstrong D., Pravda L., Al-Lazikani B., Anyango S. et al. PDBe-KB: a community-driven resource for structural and functional annotations. Nucleic Acids Res. 2020; 48: D344– D353. 31584092 PMC6943075
  14. [16]Mitsopoulos C., Di Micco P., Fernandez E.V., Dolciami D., Holt E., Mica I.L., Coker E.A., Tym J.E., Campbell J., Che K.H. et al. 2021) canSAR: update to the cancer translational research and drug discovery knowledgebase. Nucleic Acids Res. 49: D1074– D1082. 33219674 PMC7778970
  15. [17]Levy E.D., Teichmann S.A. Structural, evolutionary, and assembly principles of protein oligomerization. Progress in Molecular Biology and Translational Science. 2013; 117: Elsevier 25– 51. 23663964
  16. [18]Pravda L., Sehnal D., Svobodová Vařeková R., Navrátilová V., Toušek D., Berka K., Otyepka M., Koča J. ChannelsDB: database of biomacromolecular tunnels and pores. Nucleic Acids Res. 2018; 46: D399– D405. 29036719 PMC5753359
  17. [19]Madeira F., Tinti M., Murugesan G., Berrett E., Stafford M., Toth R., Cole C., MacKintosh C., Barton G.J. 14-3-3-Pred: improved methods to predict 14-3-3-binding phosphopeptides. Bioinformatics. 2015; 31: 2276– 2283. 25735772 PMC4495292
  18. [20]Levy E.D., Pereira-Leal J.B., Chothia C., Teichmann S.A. 3D complex: a structural classification of protein complexes. PLoS Comput. Biol. 2006; 2: e155. 17112313 PMC1636673
  19. [21]Wass M.N., Kelley L.A., Sternberg M.J.E. 3DLigandSite: predicting ligand-binding sites using similar structures. Nucleic Acids Res. 2010; 38: W469– W473. 20513649 PMC2896164
  20. [22]Parca L., Ariano B., Cabibbo A., Paoletti M., Tamburrini A., Palmeri A., Ausiello G., Helmer-Citterich M Kinome-wide identification of phosphorylation networks in eukaryotic proteomes. Bioinformatics. 2019; 35: 372– 379. 30016513 PMC6361239
  21. [23]Jubb H.C., Higueruelo A.P., Ochoa-Montaño B., Pitt W.R., Ascher D.B., Blundell T.L Arpeggio: a web server for calculating and visualising interatomic interactions in protein structures. J. Mol. Biol. 2017; 429: 365– 371. 27964945 PMC5282402
  22. [24]Sillitoe I., Dawson N., Lewis T.E., Das S., Lees J.G., Ashford P., Tolulope A., Scholes H.M., Senatorov I., Bujan A. et al. CATH: expanding the horizons of structure-based functional annotations for genome sequences. Nucleic Acids Res. 2019; 47: D280– D284. 30398663 PMC6323983
  23. [25]Tan K.P., Nguyen T.B., Patel S., Varadarajan R., Madhusudhan M.S Depth: a web server to compute depth, cavity sizes, detect potential small-molecule ligand-binding cavities and predict the pKa of ionizable residues in proteins. Nucleic Acids Res. 2013; 41: W314– W321. 23766289 PMC3692129
  24. [26]Zaidman D., Gehrtz P., Filep M., Fearon D., Gabizon R., Douangamath A., Prilusky J., Duberstein S., Cohen G., Owen C.D. et al. An automatic pipeline for the design of irreversible derivatives identifies a potent SARS-CoV-2 Mpro inhibitor. Cell Chem. Biol. 2021; 10.1016/j.chembiol.2021.05.018. PMC8228784 34174194 · DOI
  25. [27]Cilia E., Pancsa R., Tompa P., Lenaerts T., Vranken W.F The DynaMine webserver: predicting protein dynamics from sequence. Nucleic Acids Res. 2014; 42: W264– W270. 24728994 PMC4086073
  26. [28]Kumar M., Gouw M., Michael S., Sámano-Sánchez H., Pancsa R., Glavina J., Diakogianni A., Valverde J.A., Bukirova D., Čalyševa J. et al. ELM—the eukaryotic linear motif resource in 2020. Nucleic Acids Res. 2019; 48: D296– D306. PMC7145657 31680160
  27. [29]Segura J., Sanchez-Garcia R., Sorzano C.O.S., Carazo J.M 3DBIONOTES v3.0: crossing molecular and structural biology data with genomic variations. Bioinformatics. 2019; 35: 3512– 3513. 30768147 PMC6748749
  28. [30]Hopf T.A., Green A.G., Schubert B., Mersmann S., Schärfe C.P.I., Ingraham J.B., Toth-Petroczy A., Brock K., Riesselman A.J., Palmedo P. et al. The evcouplings Python framework for coevolutionary sequence analysis. Bioinformatics. 2019; 35: 1582– 1584. 30304492 PMC6499242
  29. [31]Stourac J., Dubrava J., Musil M., Horackova J., Damborsky J., Mazurenko S., Bednar D FireProtDB: database of manually curated protein stability data. Nucleic Acids Res. 2021; 49: D319– D324. 33166383 PMC7778887
  30. [32]Delgado J., Radusky L.G., Cianferoni D., Serrano L FoldX 5.0: working with RNA, small molecules and a new graphical interface. Bioinformatics. 2019; 35: 4168– 4169. 30874800 PMC6792092
  31. [33]Rausch A.O., Freiberger M.I., Leonetti C.O., Luna D.M., Radusky L.G., Wolynes P.G., Ferreiro D.U., Parra R.G FrustratometeR: an R-package to compute local frustration in protein structures, point mutants and MD simulations. Bioinformatics. 2021; 10.1093/bioinformatics/btab176. 33720293 · DOI
  32. [35]Dabrowski-Tumanski P., Rubach P., Goundaroulis D., Dorier J., Sułkowski P., Millett K.C., Rawdon E.J., Stasiak A., Sulkowska J.I KnotProt 2.0: a database of proteins with knots and other entangled structures. Nucleic Acids Res. 2019; 47: D367– D375. 30508159 PMC6323932
  33. [36]Ribeiro A.J.M., Holliday G.L., Furnham N., Tyzack J.D., Ferris K., Thornton J.M Mechanism and Catalytic Site Atlas (M-CSA): a database of enzyme reaction mechanisms and active sites. Nucleic Acids Res. 2018; 46: D618– D623. 29106569 PMC5753290
  34. [37]Putignano V., Rosato A., Banci L., Andreini C MetalPDB in 2018: a database of metal sites in biological macromolecular structures. Nucleic Acids Res. 2018; 46: D459– D464. 29077942 PMC5753354
  35. [38]Khanna T., Hanna G., Sternberg M.J.E., David A Missense3D-DB web catalogue: an atom-based analysis and repository of 4M human protein-coding genetic variants. Hum. Genet. 2021; 140: 805– 812. 33502607 PMC8052235
  36. [39]Piovesan D., Necci M., Escobedo N., Monzon A.M., Hatos A., Mičetić I., Quaglia F., Paladin L., Ramasamy P., Dosztányi Z. et al. MobiDB: intrinsically disordered proteins in 2021. Nucleic Acids Res. 2021; 49: D361– D367. 33237329 PMC7779018
  37. [40]Krivák R., Hoksza D P2Rank: machine learning based tool for rapid and accurate prediction of ligand binding sites from protein structure. J. Cheminformatics. 2018; 10: 39. PMC6091426 30109435
  38. [41]Kleinjung J., Fraternali F POPSCOMP: an automated interaction analysis of biomolecular complexes. Nucleic Acids Res. 2005; 33: W342– W346. 15980485 PMC1160130
  39. [42]McSkimming D.I., Dastgheib S., Talevich E., Narayanan A., Katiyar S., Taylor S.S., Kochut K., Kannan N ProKinO: a unified resource for mining the cancer kinome. Hum. Mutat. 2015; 36: 175– 186. 25382819 PMC4342772
  40. [43]Ramasamy P., Turan D., Tichshenko N., Hulstaert N., Vandermarliere E., Vranken W., Martens L Scop3P: a comprehensive resource of human phosphosites within their full context. J. Proteome Res. 2020; 19: 3478– 3486. 32508104
  41. [45]Tiwari S.P., Fuglebakk E., Hollup S.M., Skjærven L., Cragnolini T., Grindhaug S.H., Tekle K.M., Reuter N WEBnm@ v2.0: Web server and services for comparing protein flexibility. BMC Bioinformatics. 2014; 15: 427. 25547242 PMC4339738
  42. [46]Nair S., Váradi M., Nadzirin N., Pravda L., Anyango S., Mir S., Berrisford J., Armstrong D., Gutmanas A., Velankar S PDBe aggregated API: programmatic access to an integrative knowledge graph of molecular structure data. Bioinformatics. 2021; 10.1093/bioinformatics/btab424. PMC8570819 34081107 · DOI
  43. [47]Sehnal D., Bittrich S., Deshpande M., Svobodová R., Berka K., Bazgier V., Velankar S., Burley S.K., Koča J., Rose A.S Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures. Nucleic Acids Res. 2021; 49: W431– W437. 33956157 PMC8262734
  44. [48]Ramanathan A., Ma H., Parvatikar A., Chennubhotla S.C Artificial intelligence techniques for integrative structural biology of intrinsically disordered proteins. Curr. Opin. Struct. Biol. 2021; 66: 216– 224. 33421906
  45. [49]Waterhouse A., Bertoni M., Bienert S., Studer G., Tauriello G., Gumienny R., Heer F.T., de Beer T.A.P., Rempfer C., Bordoli L. et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 2018; 46: W296– W303. 29788355 PMC6030848
  46. [50]Mukhopadhyay A., Borkakoti N., Pravda L., Tyzack J.D., Thornton J.M., Velankar S Finding enzyme cofactors in Protein Data Bank. Bioinformatics. 2019; 35: 3510– 3511. 30759194 PMC6748742
  47. [51]Orengo C., Velankar S., Wodak S., Zoete V., Bonvin A.M.J.J., Elofsson A., Feenstra K.A., Gerloff D.L., Hamelryck T., Hancock J.M. et al. A community proposal to integrate structural bioinformatics activities in ELIXIR (3D-Bioinfo Community). F1000Research. 2020; 9: 278. PMC7284151 32566135

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Authors
PDBe-KB consortium, Varadi, M., Anyango, S., Armstrong, D., Berrisford, J., Choudhary, P., Deshpande, M., Nadzirin, N., Nair, S. S., Pravda, L., Tanweer, A., Al-Lazikani, B., Andreini, C., Barton, G. J., Bednar, D., Berka, K., Blundell, T., Brock, K. P., Carazo, J. M., Damborsky, J., David, A., Dey, S., Dunbrack, R., Recio, J. F., Fraternali, F., Gibson, T., Helmer-Citterich, M., Hoksza, D., Hopf, T., Jakubec, D., Kannan, N., Krivak, R., Kumar, M., Levy, E. D., London, N., Macias, J. R., Srivatsan, M. M., Marks, D. S., Martens, L., McGowan, S. A., McGreig, J. E., Modi, V., Parra, R. G., Pepe, G., Piovesan, D., Prilusky, J., Putignano, V., Radusky, L. G., Ramasamy, P., Rausch, A. O., Reuter, N., Rodriguez, L. A., Rollins, N. J., Rosato, A., Rubach, P., Serrano, L., Singh, G., Skoda, P., Sorzano, C. O. S., Stourac, J., Sulkowska, J. I., Svobodova, R., Tichshenko, N., Tosatto, S. C. E., Vranken, W., Wass, M. N., Xue, D., Zaidman, D., Thornton, J., Sternberg, M., Orengo, C., & Velankar, S.
ORCID
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2021-11-10
Volume
50
Issue
D1
Pages
D534-D542
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
DOI
10.1093/nar/gkab988
PMC
PMC8728252
OpenAlex
W3214131546
Cited by
82
References
4
Citations by year
2026: 9 · 2025: 13 · 2024: 19 · 2023: 17 · 2022: 23 · 2021: 1
FWCI
4.63
Type
journal article
Language
en
Open access
Licence
Locations
  • Nucleic Acids Research (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Kent Academic Repository (University of Kent) (acceptedVersion, cc-by)
  • DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion, cc-by)
  • Discovery Research Portal (University of Dundee) (submittedVersion, cc-by)
  • Florence Research (University of Florence) (submittedVersion, cc-by)
  • Cineca Institutional Research Information System (Tor Vergata University) (submittedVersion, cc-by)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
  • UCL Discovery (University College London) (submittedVersion)
  • Veřejné služby Informačního systému (Masarykiana Brunensis Universitas) (submittedVersion, cc-by)
  • Research Portal (King's College London) (submittedVersion, other-oa)
  • Repositori digital de la UPF (Universitat Pompeu Fabra) (submittedVersion, cc-by)
  • Archive ouverte UNIGE (University of Geneva) (submittedVersion, cc-by)
  • UPCommons institutional repository (Universitat Politècnica de Catalunya) (submittedVersion, cc-by)
  • VUBIR (Vrije Universiteit Brussel) (submittedVersion)
  • Padua Research Archive (University of Padova) (submittedVersion)
Funders
  • ELIXIR
  • Biotechnology and Biological Sciences Research Council (BB/T01959X/1)
  • FunPDBe (BB/P024351/1)
  • European Molecular Biology Laboratory
  • European Bioinformatics Institute
  • The Ministry of Education, Youth and Sports (INBIO CZ.02.1.01/0.0/0.0/16_026/0008451, ELIXIR-CZ LM2018131)
  • European Union's Horizon 2020 Programme (823839)
  • Research Foundation Flanders (G032816N, G042518N, G028821N)
  • Fondazione Cassa di Risparmio di Firenze (24316)
  • European Commission (101017567)
  • AIRC (IG 23539)
  • Spanish Ministry of Science and Innovation (PID2019-110167RB-I00)
  • Norwegian Research Council (288008)
  • Horizon 2020 (819318)
  • Wellcome Trust (104955/Z/14/Z, 218242/Z/19/Z)
Topics
  • Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords
Protein Data Bank, functional annotation, knowledge graphs, data exchange format, phosphorylation sites
MeSH terms
Europe, Humans, Models, Molecular, Mutation, Phosphorylation, Protein Conformation, Protein Processing, Post-Translational, Proteins, Structure-Activity Relationship, User-Computer Interface, Internet, Databases, Protein, Knowledge Bases, Molecular Sequence Annotation, Gene Ontology

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