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Pharmacological manipulation of transcription factor protein-protein interactions: opportunities and obstacles

Overview of attention for article published in Cell Regeneration, March 2015
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  • Among the highest-scoring outputs from this source (#45 of 189)
  • Good Attention Score compared to outputs of the same age (67th percentile)

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2 X users
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1 patent

Citations

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57 Dimensions

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139 Mendeley
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Title
Pharmacological manipulation of transcription factor protein-protein interactions: opportunities and obstacles
Published in
Cell Regeneration, March 2015
DOI 10.1186/s13619-015-0015-x
Pubmed ID
Authors

Frank Fontaine, Jeroen Overman, Mathias François

Abstract

Much research on transcription factor biology and their genetic pathways has been undertaken over the last 30 years, especially in the field of developmental biology and cancer. Yet, very little is known about the molecular modalities of highly dynamic interactions between transcription factors, genomic DNA, and protein partners. Methodological breakthroughs such as RNA-seq (RNA-sequencing), ChIP-seq (chromatin immunoprecipitation sequencing), RIME (rapid immunoprecipitation mass spectrometry of endogenous proteins), and single-molecule imaging will dramatically accelerate the discovery rate of their molecular mode of action in the next few years. From a pharmacological viewpoint, conventional methods used to target transcription factor activity with molecules mimicking endogenous ligands fail to achieve high specificity and are limited by a lack of identification of new molecular targets. Protein-protein interactions are likely to represent one of the next major classes of therapeutic targets. Transcription factors, known to act mostly via protein-protein interaction, may well be at the forefront of this type of drug development. One hurdle in this field remains the difficulty to collate structural data into meaningful information for rational drug design. Another hurdle is the lack of chemical libraries meeting the structural requirements of protein-protein interaction disruption. As more attempts at modulating transcription factor activity are undertaken, valuable knowledge will be accumulated on the modality of action required to modulate transcription and how these findings can be applied to developing transcription factor drugs. Key discoveries will spawn into new therapeutic approaches not only as anticancer targets but also for other indications, such as those with an inflammatory component including neurodegenerative disorders, diabetes, and chronic liver and kidney diseases.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 139 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Germany 1 <1%
Nigeria 1 <1%
Unknown 136 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 26%
Researcher 33 24%
Student > Master 13 9%
Student > Bachelor 10 7%
Student > Doctoral Student 10 7%
Other 12 9%
Unknown 25 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 56 40%
Agricultural and Biological Sciences 24 17%
Chemistry 7 5%
Pharmacology, Toxicology and Pharmaceutical Science 5 4%
Medicine and Dentistry 5 4%
Other 11 8%
Unknown 31 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 June 2018.
All research outputs
#7,960,512
of 25,374,917 outputs
Outputs from Cell Regeneration
#45
of 189 outputs
Outputs of similar age
#86,405
of 274,386 outputs
Outputs of similar age from Cell Regeneration
#1
of 1 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 189 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 74% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 274,386 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them