Evidence map›Paper›PMID 27938662›Full record

ArticleeLife2016

Transient protein-protein interactions perturb

Sanchari Bhattacharyya, Shimon Bershtein, Jin Yan, Tijda Argun, Amy I Gilson, Sunia A Trauger, Eugene I Shakhnovich

Abstract read
In one paragraph

Article in eLife, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing 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

40 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Chaperonin recognition of protein dynamics drives drug resistance.bioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Direct Quantification of Protein-Protein Interactions in Living Bacterial Cells.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  12. Article
  13. Article
  14. 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

7 authors.

Sanchari BhattacharyyaDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, United States.ORCID 0000-0003-3421-4755
Shimon BershteinDepartment of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Jin YanDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, United States.
Tijda ArgunDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, United States.
Amy I GilsonDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, United States.ORCID 0000-0003-2046-3603
Sunia A TraugerSmall Molecule Mass Spectrometry, Northwest Laboratories, Harvard University, Cambridge, United States.
Eugene I ShakhnovichDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, United States.ORCID 0000-0002-4769-2265

Funding

Study of phenotypic and fitness effects of non-functional protein interactions inR01GM111955 · NIGMS · HARVARD UNIVERSITY · PI SHAKHNOVICH, EUGENE I · 2014 to 2017
$1.4M
NIGMS NIH HHS R01 GM111955
6 · The paper itself

Abstract

Gene dosage toxicity (GDT) is an important factor that determines optimal levels of protein abundances, yet its molecular underpinnings remain unknown. Here, we demonstrate that overexpression of DHFR in

Indexed as

Gene DosageEscherichia coliEscherichia coli ProteinsMetabolomeProtein BindingProtein Interaction MapsRecombinant ProteinsTetrahydrofolate DehydrogenaseEscherichia coli ProteinsRecombinant ProteinsTetrahydrofolate Dehydrogenasebiophysicscomputational biologyE. coligene dosage toxicityprotein crowding in cytoplasmprotein-protein interactionsstructural biologysystems biology

Identifiers

PMID27938662
PMCPMC5176355

What OpenQuestion holds

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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.