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Outcome of the First wwPDB/CCDC/D3R Ligand Validation Workshop

Overview of attention for article published in Folding & Design, April 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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Citations

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Title
Outcome of the First wwPDB/CCDC/D3R Ligand Validation Workshop
Published in
Folding & Design, April 2016
DOI 10.1016/j.str.2016.02.017
Pubmed ID
Authors

Paul D. Adams, Kathleen Aertgeerts, Cary Bauer, Jeffrey A. Bell, Helen M. Berman, Talapady N. Bhat, Jeff M. Blaney, Evan Bolton, Gerard Bricogne, David Brown, Stephen K. Burley, David A. Case, Kirk L. Clark, Tom Darden, Paul Emsley, Victoria A. Feher, Zukang Feng, Colin R. Groom, Seth F. Harris, Jorg Hendle, Thomas Holder, Andrzej Joachimiak, Gerard J. Kleywegt, Tobias Krojer, Joseph Marcotrigiano, Alan E. Mark, John L. Markley, Matthew Miller, Wladek Minor, Gaetano T. Montelione, Garib Murshudov, Atsushi Nakagawa, Haruki Nakamura, Anthony Nicholls, Marc Nicklaus, Robert T. Nolte, Anil K. Padyana, Catherine E. Peishoff, Susan Pieniazek, Randy J. Read, Chenghua Shao, Steven Sheriff, Oliver Smart, Stephen Soisson, John Spurlino, Terry Stouch, Radka Svobodova, Wolfram Tempel, Thomas C. Terwilliger, Dale Tronrud, Sameer Velankar, Suzanna C. Ward, Gregory L. Warren, John D. Westbrook, Pamela Williams, Huanwang Yang, Jasmine Young

Abstract

Crystallographic studies of ligands bound to biological macromolecules (proteins and nucleic acids) represent an important source of information concerning drug-target interactions, providing atomic level insights into the physical chemistry of complex formation between macromolecules and ligands. Of the more than 115,000 entries extant in the Protein Data Bank (PDB) archive, ∼75% include at least one non-polymeric ligand. Ligand geometrical and stereochemical quality, the suitability of ligand models for in silico drug discovery and design, and the goodness-of-fit of ligand models to electron-density maps vary widely across the archive. We describe the proceedings and conclusions from the first Worldwide PDB/Cambridge Crystallographic Data Center/Drug Design Data Resource (wwPDB/CCDC/D3R) Ligand Validation Workshop held at the Research Collaboratory for Structural Bioinformatics at Rutgers University on July 30-31, 2015. Experts in protein crystallography from academe and industry came together with non-profit and for-profit software providers for crystallography and with experts in computational chemistry and data archiving to discuss and make recommendations on best practices, as framed by a series of questions central to structural studies of macromolecule-ligand complexes. What data concerning bound ligands should be archived in the PDB? How should the ligands be best represented? How should structural models of macromolecule-ligand complexes be validated? What supplementary information should accompany publications of structural studies of biological macromolecules? Consensus recommendations on best practices developed in response to each of these questions are provided, together with some details regarding implementation. Important issues addressed but not resolved at the workshop are also enumerated.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 71 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 28%
Student > Ph. D. Student 12 17%
Professor 5 7%
Student > Master 5 7%
Other 4 6%
Other 10 14%
Unknown 16 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 20 28%
Chemistry 10 14%
Agricultural and Biological Sciences 9 13%
Pharmacology, Toxicology and Pharmaceutical Science 5 7%
Computer Science 5 7%
Other 5 7%
Unknown 18 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 June 2016.
All research outputs
#3,114,500
of 25,411,814 outputs
Outputs from Folding & Design
#477
of 3,736 outputs
Outputs of similar age
#48,130
of 314,765 outputs
Outputs of similar age from Folding & Design
#11
of 43 outputs
Altmetric has tracked 25,411,814 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,736 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has done well, scoring higher than 87% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 314,765 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.