Impact of the Protein Data Bank Across Scientific Disciplines

Zukang Feng; Natalie Verdiguel; Luigi Di Costanzo; David S. Goodsell; John D. Westbrook; Stephen K. Burley; Christine Zardecki

doi:10.5334/dsj-2020-025

Data Science Journal (Jun 2020)

Impact of the Protein Data Bank Across Scientific Disciplines

Zukang Feng,
Natalie Verdiguel,
Luigi Di Costanzo,
David S. Goodsell,
John D. Westbrook,
Stephen K. Burley,
Christine Zardecki

Affiliations

Zukang Feng: Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ; Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ
Natalie Verdiguel: University of Central Florida, Orlando, Florida
Luigi Di Costanzo: Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ, US; Department of Agricultural Sciences, University of Naples Federico II, Portici
David S. Goodsell: Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ; Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA
John D. Westbrook: Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ, US; Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ
Stephen K. Burley: Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ; Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ; Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA; Rutgers Cancer Institute of New Jersey, Rutgers, The State University of New Jersey, New Brunswick, NJ; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA
Christine Zardecki: Research Collaboratory for Structural Bioinformatics Protein Data Bank, Rutgers, The State University of New Jersey, Piscataway, NJ; Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ

DOI: https://doi.org/10.5334/dsj-2020-025
Journal volume & issue: Vol. 19, no. 1

Abstract

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The Protein Data Bank archive (PDB) was established in 1971 as the 1st open access digital data resource for biology and medicine. Today, the PDB contains >160,000 atomic-level, experimentally-determined 3D biomolecular structures. PDB data are freely and publicly available for download, without restrictions. Each entry contains summary information about the structure and experiment, atomic coordinates, and in most cases, a citation to a corresponding scientific publication. Individually and in bulk, PDB structures can be downloaded and/or analyzed and visualized online using tools at RCSB.org. As such, it is challenging to understand and monitor reuse of data. Citations of the scientific publications describing PDB structures provide one way of understanding which structures are being used, and in which research areas. Our analysis highlights frequently-cited structures and identifies milestone structures that have demonstrated impact across scientific fields.

Published in Data Science Journal

ISSN: 1683-1470 (Online)
Publisher: Ubiquity Press
Country of publisher: United Kingdom
LCC subjects: Science: Science (General)
Website: http://datascience.codata.org/

About the journal

Abstract

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