Evidence map›Paper›PMID 25615855›Full record

ArticleActa crystallographica. Section D, Biological crystallography2015

Combining biophysical methods for the analysis of protein complex stoichiometry and affinity in SEDPHAT.

Huaying Zhao, Peter Schuck

Open access · hybridAbstract read
In one paragraph

Article in Acta crystallographica. Section D, Biological crystallography, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
6.1field-weighted citation impact, top 4% of its field
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

20 citing papers in PubMed, 185 citations in OpenAlex.

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  9. KEuropean biophysics journal : EBJ · 2021
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  13. Structural basis of recognition of farnesylated and methylated KRAS4b by PDEδ.Proceedings of the National Academy of Sciences of the United States of America · 2016
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  17. 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

2 authors at 2 institutions in 1 country.

Huaying ZhaoDynamics of Macromolecular Assembly Section, Laboratory of Cellular Imaging and Macromolecular Biophysics, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD 20892, USA.
Peter SchuckDynamics of Macromolecular Assembly Section, Laboratory of Cellular Imaging and Macromolecular Biophysics, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD 20892, USA.
National Institute of Biomedical Imaging and Bioengineering · USNational Institutes of Health · US

Funding

Multi-Method Approaches for the Study of Complex Protein InteractionsZIAEB000050 · NIBIB · NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING · PI SCHUCK, PETER · 2009 to 2025
$1.7M
Intramural NIH HHS
6 · The paper itself

Abstract

Reversible macromolecular interactions are ubiquitous in signal transduction pathways, often forming dynamic multi-protein complexes with three or more components. Multivalent binding and cooperativity in these complexes are often key motifs of their biological mechanisms. Traditional solution biophysical techniques for characterizing the binding and cooperativity are very limited in the number of states that can be resolved. A global multi-method analysis (GMMA) approach has recently been introduced that can leverage the strengths and the different observables of different techniques to improve the accuracy of the resulting binding parameters and to facilitate the study of multi-component systems and multi-site interactions. Here, GMMA is described in the software SEDPHAT for the analysis of data from isothermal titration calorimetry, surface plasmon resonance or other biosensing, analytical ultracentrifugation, fluorescence anisotropy and various other spectroscopic and thermodynamic techniques. The basic principles of these techniques are reviewed and recent advances in view of their particular strengths in the context of GMMA are described. Furthermore, a new feature in SEDPHAT is introduced for the simulation of multi-method data. In combination with specific statistical tools for GMMA in SEDPHAT, simulations can be a valuable step in the experimental design.

Indexed as

BiophysicsCalorimetryProtein BindingProteinsProteinsGMMASEDPHAT

Identifiers

PMID25615855
PMCPMC4304681
OpenAlexW2110093832

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.