Evidence map›Paper›PMID 24372145›Full record

ReviewExpert opinion on drug discovery2014

The future of crystallography in drug discovery.

Heping Zheng, Jing Hou, Matthew D Zimmerman, Alexander Wlodawer, Wladek Minor

Open access · greenAbstract readReview
In one paragraph

Review in Expert opinion on drug discovery, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.0field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 106 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Preparing for successful protein crystallization experiments.Acta crystallographica. Section F, Structural biology communications · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. CMM-An enhanced platform for interactive validation of metal binding sites.Protein science : a publication of the Protein Society · 2023
    Article
  11. Article
  12. Article
  13. 'International journal of molecular sciences · 2021
    Article
  14. Modelling covalent linkages in CCP4.Acta crystallographica. Section D, Structural biology · 2021
    Article
  15. Article
  16. Review
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 2 countries.

Heping ZhengUniversity of Virginia, Department of Molecular Physiology and Biological Physics , 1340 Jefferson Park Avenue, Charlottesville, VA 22908 , USA.
Jing Hou
Matthew D Zimmerman
Alexander Wlodawer
Wladek Minor
University of Virginia · USCenter for Cancer Research · USWeatherford College · US

Funding

Core H: MicrobiologyU54GM093342 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI CRONAN, JOHN E. · 2010 to 2015
$34.6M
Midwest Center for Structural GenomicsU54GM094585 · NIGMS · UNIVERSITY OF CHICAGO · PI MINOR, WLADEK · 2010 to 2014
$33.7M
The NYSGRC: A Large Scale Center for PSI:BiologyU54GM094662 · NIGMS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI ALMO, STEVEN C. · 2010 to 2014
$32.6M
Protein StructureZIABC010348 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI WLODAWER, ALEXANDER · 2009 to 2025
$27.5M
Intramural NIH HHSNIGMS NIH HHS GM093342NIGMS NIH HHS GM094585NIGMS NIH HHS GM094662NIGMS NIH HHS U54 GM093342NIGMS NIH HHS U54 GM094585NIGMS NIH HHS U54 GM094662
6 · The paper itself

Abstract

introductionX-ray crystallography plays an important role in structure-based drug design (SBDD), and accurate analysis of crystal structures of target macromolecules and macromolecule-ligand complexes is critical at all stages. However, whereas there has been significant progress in improving methods of structural biology, particularly in X-ray crystallography, corresponding progress in the development of computational methods (such as in silico high-throughput screening) is still on the horizon. Crystal structures can be overinterpreted and thus bias hypotheses and follow-up experiments. As in any experimental science, the models of macromolecular structures derived from X-ray diffraction data have their limitations, which need to be critically evaluated and well understood for structure-based drug discovery. AREAS COVERED: This review describes how the validity, accuracy and precision of a protein or nucleic acid structure determined by X-ray crystallography can be evaluated from three different perspectives: i) the nature of the diffraction experiment; ii) the interpretation of an electron density map; and iii) the interpretation of the structural model in terms of function and mechanism. The strategies to optimally exploit a macromolecular structure are also discussed in the context of 'Big Data' analysis, biochemical experimental design and structure-based drug discovery. EXPERT OPINION: Although X-ray crystallography is one of the most detailed 'microscopes' available today for examining macromolecular structures, the authors would like to re-emphasize that such structures are only simplified models of the target macromolecules. The authors also wish to reinforce the idea that a structure should not be thought of as a set of precise coordinates but rather as a framework for generating hypotheses to be explored. Numerous biochemical and biophysical experiments, including new diffraction experiments, can and should be performed to verify or falsify these hypotheses. X-ray crystallography will find its future application in drug discovery by the development of specific tools that would allow realistic interpretation of the outcome coordinates and/or support testing of these hypotheses.

Indexed as

Drug DiscoveryCrystallography, X-RayProtein ConformationProteinsProteins

Identifiers

PMID24372145
PMCPMC4106240
OpenAlexW2123058437

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.