RCSB Protein Data Bank: Enabling biomedical research and drug discovery
Abstract
Abstract Analyses of publicly available structural data reveal interesting insights into the impact of the three‐dimensional (3D) structures of protein targets important for discovery of new drugs (e.g., G‐protein‐coupled receptors, voltage‐gated ion channels, ligand‐gated ion channels, transporters, and E3 ubiquitin ligases). The Protein Data Bank (PDB) archive currently holds > 155,000 atomic‐level 3D structures of biomolecules experimentally determined using crystallography, nuclear magnetic resonance spectroscopy, and electron microscopy. The PDB was established in 1971 as the first open‐access, digital‐data resource in biology, and is now managed by the Worldwide PDB partnership (wwPDB; wwPDB.org ). US PDB operations are the responsibility of the Research Collaboratory for Structural Bioinformatics PDB (RCSB PDB). The RCSB PDB serves millions of RCSB.org users worldwide by delivering PDB data integrated with ∼40 external biodata resources, providing rich structural views of fundamental biology, biomedicine, and energy sciences. Recently published work showed that the PDB archival holdings facilitated discovery of ∼90% of the 210 new drugs approved by the US Food and Drug Administration 2010–2016. We review user‐driven development of RCSB PDB services, examine growth of the PDB archive in terms of size and complexity, and present examples and opportunities for structure‐guided drug discovery for challenging targets (e.g., integral membranemore »
- Authors:
-
[1];
[2];
[4];
[2];
[2];
[5]
- State University of New Jersey, Piscataway, NJ (United States); Rutgers Univ., Piscataway, NJ (United States); The Scripps Research Inst., La Jolla, CA (United States)
- State University of New Jersey, Piscataway, NJ (United States); Rutgers Univ., Piscataway, NJ (United States)
- State University of New Jersey, Piscataway, NJ (United States); Rutgers Univ., Piscataway, NJ (United States); Univ. of Naples Federico II (Italy)
- Univ. of California, San Diego, CA (United States)
- State University of New Jersey, Piscataway, NJ (United States); Rutgers Univ., Piscataway, NJ (United States); Univ. of California, San Diego, CA (United States); State University of New Jersey, New Brunswick, NJ (United States
- Publication Date:
- Research Org.:
- Rutgers Univ., Piscataway, NJ (United States)
- Sponsoring Org.:
- USDOE; National Science Foundation (NSF); National Institutes of Health (NIH)
- OSTI Identifier:
- 1803879
- Alternate Identifier(s):
- OSTI ID: 1576653
- Grant/Contract Number:
- SC0019749; DBI-1832184; R01GM133198; DE‐SC0019749
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Protein Science
- Additional Journal Information:
- Journal Volume: 29; Journal Issue: 1; Journal ID: ISSN 0961-8368
- Publisher:
- The Protein Society
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; biochemistry & molecular biology; protein structure and function; structural biology; Protein Data Bank; PDB; structure-guided drug discovery; integral membrane proteins; GPCR; ion channel; transporter; ubiquitin ligase
Citation Formats
Goodsell, David S., Zardecki, Christine, Di Costanzo, Luigi, Duarte, Jose M., Hudson, Brian P., Persikova, Irina, Segura, Joan, Shao, Chenghua, Voigt, Maria, Westbrook, John D., Young, Jasmine Y., and Burley, Stephen K. RCSB Protein Data Bank: Enabling biomedical research and drug discovery. United States: N. p., 2019.
Web. doi:10.1002/pro.3730.
Goodsell, David S., Zardecki, Christine, Di Costanzo, Luigi, Duarte, Jose M., Hudson, Brian P., Persikova, Irina, Segura, Joan, Shao, Chenghua, Voigt, Maria, Westbrook, John D., Young, Jasmine Y., & Burley, Stephen K. RCSB Protein Data Bank: Enabling biomedical research and drug discovery. United States. https://doi.org/10.1002/pro.3730
Goodsell, David S., Zardecki, Christine, Di Costanzo, Luigi, Duarte, Jose M., Hudson, Brian P., Persikova, Irina, Segura, Joan, Shao, Chenghua, Voigt, Maria, Westbrook, John D., Young, Jasmine Y., and Burley, Stephen K. Wed .
"RCSB Protein Data Bank: Enabling biomedical research and drug discovery". United States. https://doi.org/10.1002/pro.3730. https://www.osti.gov/servlets/purl/1803879.
@article{osti_1803879,
title = {RCSB Protein Data Bank: Enabling biomedical research and drug discovery},
author = {Goodsell, David S. and Zardecki, Christine and Di Costanzo, Luigi and Duarte, Jose M. and Hudson, Brian P. and Persikova, Irina and Segura, Joan and Shao, Chenghua and Voigt, Maria and Westbrook, John D. and Young, Jasmine Y. and Burley, Stephen K.},
abstractNote = {Abstract Analyses of publicly available structural data reveal interesting insights into the impact of the three‐dimensional (3D) structures of protein targets important for discovery of new drugs (e.g., G‐protein‐coupled receptors, voltage‐gated ion channels, ligand‐gated ion channels, transporters, and E3 ubiquitin ligases). The Protein Data Bank (PDB) archive currently holds > 155,000 atomic‐level 3D structures of biomolecules experimentally determined using crystallography, nuclear magnetic resonance spectroscopy, and electron microscopy. The PDB was established in 1971 as the first open‐access, digital‐data resource in biology, and is now managed by the Worldwide PDB partnership (wwPDB; wwPDB.org ). US PDB operations are the responsibility of the Research Collaboratory for Structural Bioinformatics PDB (RCSB PDB). The RCSB PDB serves millions of RCSB.org users worldwide by delivering PDB data integrated with ∼40 external biodata resources, providing rich structural views of fundamental biology, biomedicine, and energy sciences. Recently published work showed that the PDB archival holdings facilitated discovery of ∼90% of the 210 new drugs approved by the US Food and Drug Administration 2010–2016. We review user‐driven development of RCSB PDB services, examine growth of the PDB archive in terms of size and complexity, and present examples and opportunities for structure‐guided drug discovery for challenging targets (e.g., integral membrane proteins).},
doi = {10.1002/pro.3730},
journal = {Protein Science},
number = 1,
volume = 29,
place = {United States},
year = {Wed Sep 18 00:00:00 EDT 2019},
month = {Wed Sep 18 00:00:00 EDT 2019}
}
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