The RCSB protein data bank: integrative view of protein, gene and 3D structural information

By Peter W. Rose, Andreas Prlic, Ali Altunkaya, Chunxiao Bi, Anthony R. Bradley, Cole H. Christie, L. Costanzo, Jose M. Duarte, Shuchismita Dutta, Zukang Feng and 19 more. 2016

1,037 citations recorded by the source corpus.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, http://rcsb.org), the US data center for the global PDB archive, makes PDB data freely available to all users, from structural biologists to computational biologists and beyond. New tools and resources have been added to the RCSB PDB web portal in support of a ‘Structural View of Biology.’ Recent developments have improved the User experience, including the high-speed NGL Viewer that provides 3D molecular visualization in any web browser, improved support for data file download and enhanced organization of website pages for query, reporting and individual structure exploration. Structure validation information is now visible for all archival entries. PDB data have been integrated with external biological resources, including chromosomal position within the human genome; protein modifications; and metabolic pathways. PDB-101 educational materials have been reorganized into a searchable website and expanded to include new features such as the Geis Digital Archive.

Subfields: Materials Chemistry, Molecular Biology

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Citations in the corpus

ProDCoNN: Protein design using a convolutional neural network (2019, background): “As of November 2018, the PDB 27,28 contains 135 685 protein structures.”
Computational protein structure refinement: Almost there, yet still so far to go (2017, background): “7 Nevertheless, the number of known genes continues to greatly outnumber the number of available protein structures by orders of magnitude as experimental protein structure determination remains a slow and tedious process.”
MMTF—An efficient file format for the transmission, visualization, and analysis of macromolecular structures (2017, methodology): “For example, the 3D visualization on the RCSB PDB website is powered by MMTF [24], using the MMTF-full representation for entries 10,000 residues and the MMTF-reduced representation for larger entries.”
BRENDA, the ELIXIR core data resource in 2021: new developments and updates (2020, methodology): “The previously used viewer for enzyme 3D structures, JSMOL (26), has been replaced by the NGL viewer (27) which is more user-friendly and provides a number of additional features.”
Masked Inverse Folding with Sequence Transfer for Protein Representation Learning (2023, background): “The PDB structures used are listed in Table A1.)”
BRENDA in 2019: a European ELIXIR core data resource (2018, background): “protein sequences (UniProt, (13)), 3D structures (PDB, (14)), KEGG and MetaCyc pathways (15,16), genome annotations in the Genome Explorer (17) and links to PubMed (18) for the literature references.”
In silico methods and tools for drug discovery (2021, background): “The first step in SBDD is to obtain a high-resolution 3D structure of the target protein, which may be available in the Protein Data Bank (PDB) [135].”
RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning (2019, methodology): “The secondary structure of all the PDB sets was derived from their respective structures by using DSSR 58 software.”
PubChem 2019 update: improved access to chemical data (2018, background): “These annotations are collected from major molecular biology databases, including NCBI Gene (12), Gene Ontology (13,14), Human Genome Organization (HUGO) Gene Nomenclature Committee (HGNC) (15), UniProt (16), Protein Data Bank (PDB) (17), Conserved Domains Database (CDD) (18), Pfam (19), MedGen (20)”
AlphaFold2 versus experimental structures: evaluation on G protein-coupled receptors (2022, background): “However, due to the considerable workload and internal receptor flexibility, only 757 GPCR structures have been released to date [6, 10, 11].”
A chronotherapeutics-applicable multi-target therapeutics based on AI: Example of therapeutic hypothermia (2022, methodology): “These methods predict binding sites by matching the query structure and sequence with the ligandbinding template in BioLiP [30], which is a semi-manual functional database [31] based on the PDB.”
Rosetta FunFolDes – A general framework for the computational design of functional proteins (2018, background): “Searches for starting protein scaffolds can be achieved, but are not limited to, RMSD similarity matches to the Protein Data Bank (PDB) (Rose et al., 2017).”
An Online Resource for GPCR Structure Determination and Analysis (2019, background): “Furthermore, researchers who use GPCR structures for their studies can compare them in a way that is not possible with ‘unprocessed’ data from the RCSB Protein Data Bank (PDB) or scientific articles.”
PlantPAN3.0: a new and updated resource for reconstructing transcriptional regulatory networks from ChIP-seq experiments in plants (2018, methodology): “The Protein Data Bank (PDB) serves as a searchable platform for the 3D structures of proteins, nucleic acids, and multiprotein complexes (14,15).”