scholarly journals Crystallographic raw data, education and refereeing

2016 ◽  
Vol 62 (3) ◽  
pp. 257-261
Author(s):  
John R. Helliwell
Keyword(s):  
Experimental Data ◽  
Protein Data Bank ◽  
Structural Biology ◽  
Diffraction Data ◽  
Review Process ◽  
Data Bank ◽  
The Impact ◽  
And Training ◽  
Scientific Achievements ◽  
Future Plans

This article provides an overview of the preservation of raw diffraction data, then addresses the impact on future plans in the education and training of our community with respect to raw diffraction data and its potential reuse, and, thirdly presents the issue of referee access to the underpinning diffraction data and coordinates, as well as the Protein Data Bank Validation Report, in the review process of structural biology articles submitted for publication. Overall I pay tribute to the scientific achievements of Alex Wlodawer, who is also an ardent advocate of the importance of experimental data

scholarly journals The data universe of structural biology

IUCrJ ◽  
2020 ◽  
Vol 7 (4) ◽  
pp. 630-638 ◽  
Author(s):  
Helen M. Berman ◽  
Brinda Vallat ◽  
Catherine L. Lawson
Keyword(s):  
Protein Data Bank ◽  
Structural Biology ◽  
Data Bank ◽  
Small Data ◽  
Complex Structures ◽  
Data Resource ◽  
History Of

The Protein Data Bank (PDB) has grown from a small data resource for crystallographers to a worldwide resource serving structural biology. The history of the growth of the PDB and the role that the community has played in developing standards and policies are described. This article also illustrates how other biophysics communities are collaborating with the worldwide PDB to create a network of interoperating data resources. This network will expand the capabilities of structural biology and enable the determination and archiving of increasingly complex structures.

scholarly journals Educational Resources for Structural Biology at the RCSB Protein Data Bank

2006 ◽  
Vol 20 (4) ◽  
Author(s):  
Shuchismita Dutta ◽  
Jeff Milton ◽  
Christine Zardecki ◽  
Helen M Berman
Keyword(s):  
Protein Data Bank ◽  
Structural Biology ◽  
Data Bank ◽  
Educational Resources

MLDB: macromolecule ligand database

2009 ◽  
Vol 43 (1) ◽  
pp. 200-202 ◽  
Author(s):  
S. E. Saravanan ◽  
R. Karthi ◽  
K. Sathish ◽  
K. Kokila ◽  
R. Sabarinathan ◽  
...  
Keyword(s):  
Protein Data Bank ◽  
Structural Biology ◽  
Scientific Community ◽  
Three Dimensional ◽  
Data Bank

MLDB (macromolecule ligand database) is a knowledgebase containing ligands co-crystallized with the three-dimensional structures available in the Protein Data Bank. The proposed knowledgebase serves as an open resource for the analysis and visualization of all ligands and their interactions with macromolecular structures. MLDB can be used to search ligands, and their interactions can be visualized both in text and graphical formats. MLDB will be updated at regular intervals (weekly) with automated Perl scripts. The knowledgebase is intended to serve the scientific community working in the areas of molecular and structural biology. It is available free to users around the clock and can be accessed at http://dicsoft2.physics.iisc.ernet.in/mldb/.

scholarly journals Worldwide Protein Data Bank biocuration supporting open access to high-quality 3D structural biology data

Database ◽  
2018 ◽  
Vol 2018 ◽  
Author(s):  
Jasmine Y Young ◽  
John D Westbrook ◽  
Zukang Feng ◽  
Ezra Peisach ◽  
Irina Persikova ◽  
...  
Keyword(s):  
Open Access ◽  
Protein Data Bank ◽  
Structural Biology ◽  
Data Bank ◽  
High Quality

scholarly journals The RCSB Protein Data Bank: views of structural biology for basic and applied research and education

2014 ◽  
Vol 43 (D1) ◽  
pp. D345-D356 ◽  
Author(s):  
Peter W. Rose ◽  
Andreas Prlić ◽  
Chunxiao Bi ◽  
Wolfgang F. Bluhm ◽  
Cole H. Christie ◽  
...  
Keyword(s):  
Protein Data Bank ◽  
Structural Biology ◽  
Applied Research ◽  
Data Bank ◽  
Basic And Applied Research ◽  
Research And Education

scholarly journals Analysis of crystallization data in the Protein Data Bank

2015 ◽  
Vol 71 (10) ◽  
pp. 1228-1234 ◽  
Author(s):  
Jobie Kirkwood ◽  
David Hargreaves ◽  
Simon O'Keefe ◽  
Julie Wilson
Keyword(s):  
Experimental Data ◽  
Protein Data Bank ◽  
Isoelectric Point ◽  
Protein Structures ◽  
Data Bank ◽  
Solution Ph

The Protein Data Bank (PDB) is the largest available repository of solved protein structures and contains a wealth of information on successful crystallization. Many centres have used their own experimental data to draw conclusions about proteins and the conditions in which they crystallize. Here, data from the PDB were used to reanalyse some of these results. The most successful crystallization reagents were identified, the link between solution pH and the isoelectric point of the protein was investigated and the possibility of predicting whether a protein will crystallize was explored.

L-Fucose in Crystal Structures of IgG-Fc: Reinterpretation of Experimental Data

2008 ◽  
Vol 73 (5) ◽  
pp. 608-615 ◽  
Author(s):  
Petr Kolenko ◽  
Tereza Skálová ◽  
Jan Dohnálek ◽  
Jindřich Hašek
Keyword(s):  
Experimental Data ◽  
Immune System ◽  
Protein Data Bank ◽  
Electron Density ◽  
Data Bank ◽  
System Response ◽  
Fc Fragment ◽  
Effector Functions ◽  
Immune System Response ◽  
Good Agreement

Glycosylation of IgG-Fc plays an important role in the activation of the immune system response. Effector functions are modulated by different degrees of deglycosylation of IgG-Fc. However, the geometry of oligosaccharides covalently bound to IgG-Fc does not seem to be in good agreement with electron density in most of the structures deposited in the Protein Data Bank. Our study of correlation between the oligosaccharide geometry, connectivity, and electron density shows several discrepancies, mainly for L-fucose. Revision of refinement of two structures containing the Fc-fragment solved at the highest resolution brings clear evidence for α-L-fucosylation instead of β-L-fucosylation as it was claimed in most of the deposited structures in the Protein Data Bank containing the Fc-fragment, and also in the original structures selected for re-refinement. Our revision refinement results in a decrease in R factors, better agreement with electron density, meaningful contacts, and acceptable geometry of L-fucose.

scholarly journals Making glycoproteins a little bit sweeter withPDB-REDO

2018 ◽  
Vol 74 (8) ◽  
pp. 463-472 ◽  
Author(s):  
Bart van Beusekom ◽  
Thomas Lütteke ◽  
Robbie P. Joosten
Keyword(s):  
Experimental Data ◽  
Amino Acid ◽  
Protein Data Bank ◽  
Model Building ◽  
Data Bank ◽  
Structure Model ◽  
Amino Acid Residues ◽  
Post Translational Modification ◽  
High Quality ◽  
Glycoprotein Structure

Glycosylation is one of the most common forms of protein post-translational modification, but is also the most complex. Dealing with glycoproteins in structure model building, refinement, validation and PDB deposition is more error-prone than dealing with nonglycosylated proteins owing to limitations of the experimental data and available software tools. Also, experimentalists are typically less experienced in dealing with carbohydrate residues than with amino-acid residues. The results of the reannotation and re-refinement byPDB-REDOof 8114 glycoprotein structure models from the Protein Data Bank are analyzed. The positive aspects of 3620 reannotations and subsequent refinement, as well as the remaining challenges to obtaining consistently high-quality carbohydrate models, are discussed.

scholarly journals A public database of macromolecular diffraction experiments

2016 ◽  
Vol 72 (11) ◽  
pp. 1181-1193 ◽  
Author(s):  
Marek Grabowski ◽  
Karol M. Langner ◽  
Marcin Cymborowski ◽  
Przemyslaw J. Porebski ◽  
Piotr Sroka ◽  
...  
Keyword(s):  
Experimental Data ◽  
Diffraction Data ◽  
Distributed Storage ◽  
Protein Structure Determination ◽  
Data Bank ◽  
Scientific Integrity ◽  
Biological Macromolecules ◽  
Data Sets ◽  
X Ray ◽  
Unrestricted Access

The low reproducibility of published experimental results in many scientific disciplines has recently garnered negative attention in scientific journals and the general media. Public transparency, including the availability of `raw' experimental data, will help to address growing concerns regarding scientific integrity. Macromolecular X-ray crystallography has led the way in requiring the public dissemination of atomic coordinates and a wealth of experimental data, making the field one of the most reproducible in the biological sciences. However, there remains no mandate for public disclosure of the original diffraction data. The Integrated Resource for Reproducibility in Macromolecular Crystallography (IRRMC) has been developed to archive raw data from diffraction experiments and, equally importantly, to provide related metadata. Currently, the database of our resource contains data from 2920 macromolecular diffraction experiments (5767 data sets), accounting for around 3% of all depositions in the Protein Data Bank (PDB), with their corresponding partially curated metadata. IRRMC utilizes distributed storage implemented using a federated architecture of many independent storage servers, which provides both scalability and sustainability. The resource, which is accessibleviathe web portal at http://www.proteindiffraction.org, can be searched using various criteria. All data are available for unrestricted access and download. The resource serves as a proof of concept and demonstrates the feasibility of archiving raw diffraction data and associated metadata from X-ray crystallographic studies of biological macromolecules. The goal is to expand this resource and include data sets that failed to yield X-ray structures in order to facilitate collaborative efforts that will improve protein structure-determination methods and to ensure the availability of `orphan' data left behind for various reasons by individual investigators and/or extinct structural genomics projects.

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