Announcing the worldwide Protein Data Bank
By Helen M. Berman, K. Henrick, Haruki Nakamura. 2003
2,921 citations recorded by the source corpus.
Subfields: Materials Chemistry, Molecular Biology, Spectroscopy, Evaluation & Benchmarks, Computational Biology & Bioinformatics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Materials Chemistry
- Torsten Schwede
- Ben M. Webb
- Andrej Sali
- Yang Zhang
- Andriy Kryshtafovych
- Randy J. Read
- David Baker
- Gaetano T. Montelione
In Molecular Biology
- Torsten Schwede
- Yang Zhang
- Andrej Sali
- Ben M. Webb
- Andriy Kryshtafovych
- David Baker
- Jinbo Xu
- Björn Wallner
In Spectroscopy
- Burkhard Rost
- Sean R. Eddy
- David T. Jones
- Andriy Kryshtafovych
- Randy J. Read
- G. Bunkoczi
- Torsten Schwede
- Björn Wallner
In Evaluation & Benchmarks
- Torsten Schwede
- Andriy Kryshtafovych
- Björn Wallner
- Andrej Sali
- Yang Zhang
- Randy J. Read
- Chaok Seok
- Krzysztof Fidelis
In Computational Biology & Bioinformatics
- Torsten Schwede
- Yang Zhang
- Björn Wallner
- Burkhard Rost
- Andriy Kryshtafovych
- Jinbo Xu
- Ben M. Webb
- Mohammed Alquraishi
Citations in the corpus
- DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking (2022, methodology): “We use the molecular complexes in PDBBind [12] that were extracted from the Protein Data Bank (PDB) [13].”
- EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction (2022, methodology): “Due to the differences in resolution and the average ligand size (32 heavy atoms in PDBBind versus 24 in the core set), the complexes of the core set can be considered easier to predict than the average complex.”
- The Pfam protein families database in 2019 (2018, background): “Figure 1 shows the change in the domain boundaries for PF17262 and the addition of the PF17955 entry between Pfam 31.0 and Pfam 32.0, on PDB structure PDB: 4z7k.”
- Local Error Estimates Dramatically Improve the Utility of Homology Models for Solving Crystal Structures by Molecular Replacement (2015, methodology): “Predictions were evaluated with three B-factor schemes: (a) B factors as present in the PDB file, (b) B factors calculated assuming that the submitted values are expected errors, using Equation 1, and (c) constant B factors.”
- Protein data bank (2012, background): “The RCBS PDB and PDBj presently act as an archive centre for wwPDB .[4] The wwPDB’s mission is to maintain a single PDB archive of macromolecular structural data that is freely and publicly available to the global community.”
- Outcome of a Workshop on Applications of Protein Models in Biomedical Research (2009, background): “Membership of this group should consist of a representative of the wwPDB (Berman et al., 2003), the Protein Model Portal, as well as members of the modeling and user communities.”
- Multicoil2: Predicting Coiled Coils and Their Oligomerization States from Sequence in the Twilight Zone (2011, methodology): “The first line contains the protein name or PDB-id and BLAST E-value to the query (plus query name), where appropriate.”
- The RCSB PDB information portal for structural genomics (2005, background): “30 The wwPDB ( 1 ) maintains the Protein Data Bank (PDB) archives of biological macromolecular structure data, currently comprising over 32 500 structures.”
- VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data (2011, methodology): “Files in the Protein Data Bank (*.pdb) format (Berman et al., 2003) and the XCrySDen *.xsf format (Kokalj, 2003) can now be input more reliably.”
- Outcome of the First wwPDB Hybrid/Integrative Methods Task Force Workshop (2015, neutral): “Over the past several years, the Worldwide Protein Data Bank (wwPDB; the global organization responsible for maintaining the PDB archive) (Berman et al., 2003) has established expert, methodspecific Task Forces to advise on which experimental data and metadata from each method should be archived and”
- RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning (2022, background): “org) partnership (50,51), which has jointly managed the Protein Data Bank archive since 2003.”
- The Uppsala Electron-Density Server. (2004, background): “However, in the macromolecular-structure world we are fortunate to have one single uniform database in the form of the Worldwide PDB (Berman et al., 2003).”