Evidence map›Paper›PMID 28436492›Full record

ArticleNature communications2017

A multi-crystal method for extracting obscured crystallographic states from conventionally uninterpretable electron density.

Nicholas M Pearce, Tobias Krojer, Anthony R Bradley, Patrick Collins, Radosław P Nowak, Romain Talon, Brian D Marsden, Sebastian Kelm, Jiye Shi, Charlotte M Deane and 1 more

Abstract read
In one paragraph

Article in Nature communications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 199 papers.

0numbers the graph read from it
0cells of the map it votes in
199citing papers in PubMed
–field-weighted citation impact
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

199 citing papers in PubMed.

  1. Article
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  5. Avoiding pitfalls when modelling ligands in macromolecular crystallography.Acta crystallographica. Section D, Structural biology · 2026
    Article
  6. Review
  7. Article
  8. Article
  9. Scotty: lattice coincidences for macromolecular crystallographic phasing.Acta crystallographica. Section D, Structural biology · 2026
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. The Untangle Challenge for accurate ensemble models.bioRxiv : the preprint server for biology · 2026
    Article
  20. CACHE Challenge #3: Targeting the Nsp3 Macrodomain of SARS-CoV-2.Journal of chemical information and modeling · 2026
    Article

139 more citing papers are in PubMed but not listed here.

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

11 authors.

Nicholas M PearceStructural Genomics Consortium, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford OX3 7DQ, UK.
Tobias KrojerStructural Genomics Consortium, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford OX3 7DQ, UK.
Anthony R BradleyStructural Genomics Consortium, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford OX3 7DQ, UK.
Patrick CollinsDiamond Light Source Ltd, Harwell Science and Innovation Campus, Didcot OX11 0QX, UK.ORCID 0000-0002-6265-9922
Radosław P NowakStructural Genomics Consortium, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford OX3 7DQ, UK.
Romain TalonStructural Genomics Consortium, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford OX3 7DQ, UK.
Brian D MarsdenStructural Genomics Consortium, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford OX3 7DQ, UK.
Sebastian KelmUCB Pharma, 208 Bath Road, Slough SL1 3WE, UK.
Jiye ShiUCB Pharma, 208 Bath Road, Slough SL1 3WE, UK.
Charlotte M DeaneDepartment of Statistics, University of Oxford, 24-29 St Giles, Oxford OX1 3LB, UK.ORCID 0000-0003-1388-2252
Frank von DelftStructural Genomics Consortium, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford OX3 7DQ, UK.ORCID 0000-0003-0378-0017

Funding

Wellcome Trust
6 · The paper itself

Abstract

In macromolecular crystallography, the rigorous detection of changed states (for example, ligand binding) is difficult unless signal is strong. Ambiguous ('weak' or 'noisy') density is experimentally common, since molecular states are generally only fractionally present in the crystal. Existing methodologies focus on generating maximally accurate maps whereby minor states become discernible; in practice, such map interpretation is disappointingly subjective, time-consuming and methodologically unsound. Here we report the PanDDA method, which automatically reveals clear electron density for the changed state-even from inaccurate maps-by subtracting a proportion of the confounding 'ground state'; changed states are objectively identified from statistical analysis of density distributions. The method is completely general, implying new best practice for all changed-state studies, including the routine collection of multiple ground-state crystals. More generally, these results demonstrate: the incompleteness of atomic models; that single data sets contain insufficient information to model them fully; and that accuracy requires further map-deconvolution approaches.

Identifiers

PMID28436492
PMCPMC5413968

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Registered trials

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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.