Evidence map›Paper›PMID 20142515›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2010

Heterospecies partition analysis reveals binding curve and stoichiometry of protein interactions in living cells.

Bin Wu, Yan Chen, Joachim D Müller

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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  6. Fluorescence Imaging Methods to Investigate Translation in Single Cells.Cold Spring Harbor perspectives in biology · 2019
    Review
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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

3 authors.

Bin WuSchool of Physics and Astronomy, University of Minnesota, Minneapolis, MN 55455, USA.
Yan Chen
Joachim D Müller

Funding

In vivo Fluorescence Fluctuation Spectroscopy - Administrative SupplementR01GM064589 · NIGMS · UNIVERSITY OF MINNESOTA TWIN CITIES · PI MUELLER, JOACHIM D · 2002 to 2019
$4.6M
NIGMS NIH HHS GM64589NIGMS NIH HHS R01 GM064589
6 · The paper itself

Abstract

Measuring the binding curve and stoichiometry of protein complexes in living cells is a prerequisite for quantitative modeling of cellular processes. Dual-color fluorescence fluctuation spectroscopy provides a general framework for detecting protein interactions, but lacks suitable methods for quantifying protein heterointeractions in the cell. We address this challenge by introducing heterospecies partition (HSP) analysis for protein heterointeractions of the type D + nA<-->DA(n). HSP directly identifies the heterointeracting species from the sample mixture and determines the binding curve and stoichiometry of the protein complex. The HSP method is applied to provide the first direct characterization of the ligand-dependent binding of the retinoic X receptor to the coactivator transcription intermediate factor 2. A previous study based on protein fragments observed a higher binding stoichiometry than biologically expected. We address this difference in stoichiometry by measuring the binding curves of the full-length proteins in living cells. This study provides proof-of-principle experiments that illustrate the potential of HSP as a general and robust analysis tool for the quantitative characterization of protein heterointeractions by dual-color fluorescence fluctuation spectroscopy in living cells.

Indexed as

DimerizationFluorescence Resonance Energy TransferMicroscopy, FluorescenceModels, MolecularProtein BindingRetinoid X ReceptorsRetinoid X Receptors

Identifiers

PMID20142515
PMCPMC2840129

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.