Evidence map›Paper›PMID 27111507›Full record

ArticleNature methods2016

Automated structure modeling of large protein assemblies using crosslinks as distance restraints.

Mathias Ferber, Jan Kosinski, Alessandro Ori, Umar J Rashid, María Moreno-Morcillo, Bernd Simon, Guillaume Bouvier, Paulo Ricardo Batista, Christoph W Müller, Martin Beck and 1 more

Abstract read
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In one paragraph

Article in Nature methods, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

  1. Article
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  4. Review
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  6. Article
  7. Review
  8. Automatic Bayesian Weighting for SAXS Data.Frontiers in molecular biosciences · 2021
    Article
  9. High-density chemical cross-linking for modeling protein interactions.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Rapid Mapping of Protein Interactions Using Tag-Transfer Photocrosslinkers.Angewandte Chemie (International ed. in English) · 2018
    Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. Review
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.

Mathias FerberInstitut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, Paris, France.
Jan KosinskiEuropean Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.ORCID 0000-0002-3641-0322
Alessandro OriEuropean Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.ORCID 0000-0002-3046-0871
Umar J RashidEuropean Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.
María Moreno-MorcilloEuropean Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.
Bernd SimonEuropean Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.
Guillaume BouvierInstitut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, Paris, France.
Paulo Ricardo BatistaInstitut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, Paris, France.ORCID 0000-0002-3399-174X
Christoph W MüllerEuropean Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.ORCID 0000-0003-2176-8337
Martin BeckEuropean Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany.ORCID 0000-0002-7397-1321
Michael NilgesInstitut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3528, Département de Biologie Structurale et Chimie, Paris, France.ORCID 0000-0002-1451-8092

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Crosslinking mass spectrometry is increasingly used for structural characterization of multisubunit protein complexes. Chemical crosslinking captures conformational heterogeneity, which typically results in conflicting crosslinks that cannot be satisfied in a single model, making detailed modeling a challenging task. Here we introduce an automated modeling method dedicated to large protein assemblies ('XL-MOD' software is available at http://aria.pasteur.fr/supplementary-data/x-links) that (i) uses a form of spatial restraints that realistically reflects the distribution of experimentally observed crosslinked distances; (ii) automatically deals with ambiguous and/or conflicting crosslinks and identifies alternative conformations within a Bayesian framework; and (iii) allows subunit structures to be flexible during conformational sampling. We demonstrate our method by testing it on known structures and available crosslinking data. We also crosslinked and modeled the 17-subunit yeast RNA polymerase III at atomic resolution; the resulting model agrees remarkably well with recently published cryoelectron microscopy structures and provides additional insights into the polymerase structure.

Indexed as

Models, TheoreticalBayes TheoremCross-Linking ReagentsMass SpectrometryMultiprotein ComplexesProtein ConformationProtein SubunitsReproducibility of ResultsRNA Polymerase IIISaccharomyces cerevisiae ProteinsSensitivity and SpecificityCross-Linking ReagentsMultiprotein ComplexesProtein SubunitsRNA Polymerase IIISaccharomyces cerevisiae Proteins

Identifiers

PMID27111507

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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.