Evidence map›Paper›PMID 29665372›Full record

ArticleJournal of molecular biology2018

Integrating Cross-Linking Experiments with Ab Initio Protein-Protein Docking.

Thom Vreven, Devin K Schweppe, Juan D Chavez, Chad R Weisbrod, Sayaka Shibata, Chunxiang Zheng, James E Bruce, Zhiping Weng

Abstract read
In one paragraph

Article in Journal of molecular biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Mapping the interaction surface between CaNature communications · 2025
    Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Advances to tackle backbone flexibility in protein docking.Current opinion in structural biology · 2021
    Review
  8. Docking approaches for modeling multi-molecular assemblies.Current opinion in structural biology · 2020
    Review
  9. Article
  10. High-density chemical cross-linking for modeling protein interactions.Proceedings of the National Academy of Sciences of the United States of America · 2020
    Article
  11. Article
  12. What method to use for protein-protein docking?Current opinion in structural biology · 2019
    Review
  13. 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

8 authors.

Thom VrevenProgram in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA. Electronic address: Thom.Vreven@umassmed.edu.
Devin K SchweppeDepartment of Chemistry and Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
Juan D ChavezDepartment of Chemistry and Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
Chad R WeisbrodDepartment of Chemistry and Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
Sayaka ShibataDepartment of Chemistry and Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
Chunxiang ZhengDepartment of Chemistry and Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
James E BruceDepartment of Chemistry and Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
Zhiping WengProgram in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA. Electronic address: Zhiping.Weng@umassmed.edu.

Funding

Protein Interaction Technology CoreU19AI107775 · NIAID · UNIVERSITY OF WASHINGTON · PI BRITTNACHER, MITCHELL J · 2013 to 2017
$7.7M
Quantitation of protein interactions in cancer cellsR01GM086688 · NIGMS · UNIVERSITY OF WASHINGTON · PI BRUCE, JAMES EDWARD · 2009 to 2019
$4.2M
Template-based docking refinement approach to protein-protein structure modelingR01GM116960 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2016 to 2019
$1.4M
NIAID NIH HHS U19 AI107775NIGMS NIH HHS R01 GM086688NIGMS NIH HHS R01 GM116960
6 · The paper itself

Abstract

Ab initio protein-protein docking algorithms often rely on experimental data to identify the most likely complex structure. We integrated protein-protein docking with the experimental data of chemical cross-linking followed by mass spectrometry. We tested our approach using 19 cases that resulted from an exhaustive search of the Protein Data Bank for protein complexes with cross-links identified in our experiments. We implemented cross-links as constraints based on Euclidean distance or void-volume distance. For most test cases, the rank of the top-scoring near-native prediction was improved by at least twofold compared with docking without the cross-link information, and the success rate for the top 5 predictions nearly tripled. Our results demonstrate the delicate balance between retaining correct predictions and eliminating false positives. Several test cases had multiple components with distinct interfaces, and we present an approach for assigning cross-links to the interfaces. Employing the symmetry information for these cases further improved the performance of complex structure prediction.

Indexed as

AlgorithmsComputational BiologyCross-Linking ReagentsDatabases, ProteinModels, MolecularMolecular Docking SimulationProtein BindingProtein ConformationProteinsCross-Linking ReagentsProteinsmass spectrometryprotein–protein complexstructuresymmetryZDOCK

Identifiers

PMID29665372
PMCPMC6084434

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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.