\the Protein Data Bank: a Computer-based Archival Le 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

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Recent advances in de novo protein design: Principles, methods, and applications (2021, methodology): “The ﬁ rst version of the scoring function in the Rosetta program for structural modeling, and the design was developed for protein structure prediction (115) and was a statistical potential function derived from structures in the PDB (16, 116) using Bayesian statistics (35).”
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).”
Improved recognition of native‐like protein structures using a combination of sequence‐dependent and sequence‐independent features of proteins (1999, methodology): “24 All the statistics of this work were taken from a nonredundant subset (pdb_select25 25 ) of the Brookhaven database.”
Automatic rebuilding and optimization of crystallographic structures in the Protein Data Bank (2011, background): “D ow nloaded from https://academ ic.oup.com /bioinform atics/article-abstract/27/24/3392/306825 by guest on 30 O ctober 2018 [12:43 12/11/2011 Bioinformatics-btr590.tex] Page: 3393 3392–3398 Most available validation tools have their own limitations.”
Torsion angle dynamics for NMR structure calculation with the new program DYANA. (1997, methodology): “Data ®le formats are compatible with the programs XEASY (Bartels et al., 1995), GARANT (Bartels et al., 1997), DIANA (Gu È ntert et al., 1991a), MOLMOL (Koradi et al., 1996), OPAL (Luginbu È hl et al., 1996), XPLOR (Bru È nger, 1992), and with the Brookhaven Protein Data Bank (Bernstein et al., 1977”
Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling tool. (1997, methodology): “Protein structures were taken from the August 1996 update of the Brookhaven Protein Databank (Bernstein et al., 1977).”
Better prediction of sub‐cellular localization by combining evolutionary and structural information (2003, methodology): “Next, we assigned localization to PDB chains 56 by searching for homologues in the “trusted SWISS-PROT set.””
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): “5 AÊ ) and re®ned proteins from the Brookhaven databank (Bernstein et al., 1997), with less than 20% sequence identity or no structural homology. A list of these proteins can be found in Wintjens et al. (1996). To avoid biasing the predictions towards the native structure, the potentials are derived”
Serine and Threonine Residues Bend α-Helices in the χ1 = g− Conformation (2000, methodology): “1 (Oxford Molecular) was used for the selection of protein structures in the Brookhaven Protein DataBank (Bernstein et al., 1977).”