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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes
Published on: May 22, 2018
Trendspotting in the Protein Data Bank
Helen M Berman1, Buvaneswari Coimbatore Narayanan, Luigi Di Costanzo
1Department of Chemistry and Chemical Biology, Center for Integrative Proteomics Research, Rutgers, The State University of New Jersey, 174 Frelinghuysen Road, Piscataway, NJ 08854-8076, USA. berman@rcsb.rutgers.edu
The Protein Data Bank (PDB) archives over 85,000 macromolecule structures. Analyzing this data reveals trends to guide the future of structural biology and PDB data management.
Area of Science:
- Structural biology
- Biochemistry
- Bioinformatics
Background:
- The Protein Data Bank (PDB) was founded in 1971.
- It serves as a global archive for 3D structures of biological macromolecules.
- Over 85,000 structures are currently available.
Purpose of the Study:
- To analyze trends within the PDB archive.
- To inform the future direction of structural biology research.
- To optimize the management of the growing PDB dataset.
Main Methods:
- Data mining of the Protein Data Bank archive.
- Trend analysis of structural biology data.
- Bibliometric and structural data analysis.
Main Results:
- Identification of key trends in macromolecular structure determination.
- Insights into the evolution of structural biology.
- Assessment of current data management strategies.
Conclusions:
- Analysis of PDB data provides valuable insights for future research.
- Strategic planning is essential for managing large-scale biological data.
- Understanding historical trends aids in advancing structural biology.
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