The Protein Data Bank: a computer-based archival file for macromolecular structures.

By F. C. Bernstein, T. Koetzle, G. J. Williams, E. Meyer, M. Brice, J. Rodgers, T. P. Singh, T. Shimanouchi, M. Tasumi. 1977

Subfields: 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 Evaluation & Benchmarks

1. Torsten Schwede
2. Anna Tramontano
3. Randy J. Read
4. Yang Zhang
5. Mohammed Alquraishi
6. Krzysztof Fidelis
7. Gaetano T. Montelione
8. John Moult

In Computational Biology & Bioinformatics

1. Yang Zhang
2. Burkhard Rost
3. Torsten Schwede
4. David T. Jones
5. Jinbo Xu
6. Arne Elofsson
7. David Baker
8. Mohammed Alquraishi

Citations in the corpus

• Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix (2019, methodology): “Of the models deposited in the Protein Data Bank (PDB; Bernstein et al., 1977; Burley et al., 2019), 89% originate from X-ray crystallography.”
• Towards automated crystallographic structure refinement with phenix.refine (2012, methodology): “The PDB format (Bernstein et al., 1977; Berman et al., 2000) is the most commonly used format for exchanging macromolecular model data and is therefore available as the input format for refinement in PHENIX.”
• Features and development of Coot (2010, neutral): “(i) Protein Data Bank (PDB) format (with file extension .pdb or .ent ; compressed files of this format with extension .gz can also be read).”
• The Pfam protein families database (2007, background): “Whenever an article is found to contain a PDB identifier, we will use the Web services to retrieve the abstract, figures and figure legends from that article and make them available on our pages.”
• BindingDB: a web-accessible database of experimentally determined protein–ligand binding affinities (2006, background): “Data collection currently focuses on targets whose threedimensional structures are available in the Protein Data Bank (5,6) (PDB) or can be accurately modeled.”
• ProteinNet: a standardized data set for machine learning of protein structure (2019, methodology): “Repositories such as the Protein Data Bank (PDB) [9] provide raw protein structures, but require postprocessing before they are usable by machine learning frameworks.”
• Real-space refinement in PHENIX for cryo-EM and crystallography (2018, methodology): “3.2 Refinement using data from PDB and EMDB 3.2.1 Default refinement In order to test the methods and demonstrate their utility we re-refined 385 cryo-EM models from the PDB that are reported at resolution 6 Å or better, that have model-map correlation greater than 0.3 and that contain only residues”
• Predicting protein stability changes upon mutation using database-derived potentials: solvent accessibility determines the importance of local versus non-local interactions along the sequence. (1997, methodology): “…B C 49.7 62 Arg Ala B C 44.4 77 Ala Gly C C 40.7 Chicken 68 Arg Lys C S 44.8 lysozyme (4LYZ) a The codes in parentheses correspond to the PDB codes (Bernstein et al., 1977) of the proteins. b The (f,c,o) domains of the mutated residues in the wild-type structure, using de®nitions of Rooman et…”
• Potential of quantum computing for drug discovery (2018, background): “A typical prediction with comparative modeling implies the identification of related proteins that can serve as templates from a database of known structures, usually the Protein Data Bank [31].”
• Protein flexibility and rigidity predicted from sequence (2005, methodology): “We obtained multiple sequence alignments by searching with PSI-BLAST 47 against all known sequences contained in SWISS-PROT, 62 TrEMBL, 62 and PDB. 30,31 All hits below a PSI-BLAST E -value of 10 ) 3 were subsequently filtered 44,48 and included in the sequence profile.”
• De novo protein design: towards fully automated sequence selection. (1997, methodology): “The Brookhaven Protein Data Bank (PDB) (Bernstein et al., 1977) was examined for high resolution structures of the bba motif, and the second zinc ®nger module of the DNA binding protein Zif268 (PDB code 1zaa) was selected as our design template (Pavletich & Pabo, 1991).”
• Statistical potentials extracted from protein structures: how accurate are they? (1996, methodology): “First, amino acid pair density functions rij (r) are constructed by summing the static densities observed in different proteins from the Brookhaven Protein Data Bank (PDB, Bernstein et al., 1977) rather than averaging different states of the same protein.”