PDBFlex: exploring flexibility in protein structures
By Thomas Hrabe, Jim Zhanwen Li, Mayya Sedova, Piotr Rotkiewicz, Lukasz Jaroszewski, Adam Godzik. 2015
85 citations recorded by the source corpus.
The PDBFlex database, available freely and with no login requirements at http://pdbflex.org, provides information on flexibility of protein structures as revealed by the analysis of variations between depositions of different structural models of the same protein in the Protein Data Bank (PDB). PDBFlex collects information on all instances of such depositions, identifying them by a 95% sequence identity threshold, performs analysis of their structural differences and clusters them according to their structural similarities for easy analysis. The PDBFlex contains tools and viewers enabling in-depth examination of structural variability including: 2D-scaling visualization of RMSD distances between structures of the same protein, graphs of average local RMSD in the aligned structures of protein chains, graphical presentation of differences in secondary structure and observed structural disorder (unresolved residues), difference distance maps between all sets of coordinates and 3D views of individual structures and simulated transitions between different conformations, the latter displayed using JSMol visualization software.
Subfields: Materials Chemistry, Molecular Biology
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In Materials Chemistry
- Stephen K. Burley
- John D. Westbrook
- Christine Zardecki
- David S. Goodsell
- Shuchismita Dutta
- Andreas Prlic
- Alexander Rives
- Helen M. Berman
In Molecular Biology
- Stephen K. Burley
- John D. Westbrook
- David S. Goodsell
- Christine Zardecki
- Shuchismita Dutta
- Brian L. Hie
- Andreas Prlic
- Alexander Rives
Citations in the corpus
- Learning inverse folding from millions of predicted structures (2022, methodology): “We compare single-state and multi-state sequence design performance on 87 test split proteins with multiple conformations in the PDBFlex dataset (Hrabe et al., 2016).”
- RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy (2018, methodology): “Information regarding structural variation represented in similar amino acid sequences has been available through the integration of PDB structures with data from the PDBFlex database (39).”
- RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning (2022, unknown): “PDBflex (101) Protein structure flexibility”