Title |
Outcome of the First wwPDB/CCDC/D3R Ligand Validation Workshop
|
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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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 6 | 33% |
United Kingdom | 3 | 17% |
Japan | 2 | 11% |
Unknown | 7 | 39% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 10 | 56% |
Scientists | 7 | 39% |
Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 1 | 1% |
Unknown | 71 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
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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% |