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Modulation of coiled-coil dimer stability through surface residues while preserving pairing specificity

Overview of attention for article published in Journal of the American Chemical Society
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

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11 tweeters

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29 Mendeley
Title
Modulation of coiled-coil dimer stability through surface residues while preserving pairing specificity
Published in
Journal of the American Chemical Society
DOI 10.1021/jacs.7b01690
Pubmed ID
Authors

Igor Drobnak, Helena Gradišar, Ajasja Ljubetič, Estera Merljak, Roman Jerala

Abstract

The coiled-coil dimer is a widespread protein structural motif and due to its designability represents an attractive building block for assembling modular nanostructures. The specificity of coiled-coil dimer pairing is mainly based on the hydro-phobic and electrostatic interactions between residues at positions a and d, and e and g of the heptad repeat, respectively. Binding affinity, on the other hand, can also be affected by surface residues that face away from the dimerization interface. Here we show how design of the local helical propensity of interacting peptides can be used to tune the stabilities of coiled-coil dimers over a wide range. By designing intramolecular charge pairs, regions of high local helical propensity can be engineered to form trigger sequences and dimer stability is adjusted without changing the peptide length or any of the directly interacting residues. This general principle is demonstrated by a change in thermal stability by more than 30 °C as a result of only two mutations outside the binding interface. The same approach was successfully used to modulate the stabilities in an orthogonal set of coiled-coils without affecting their binding preferences. The stability effects of local helical propensity and peptide charge are well described by a simple linear model, which should help improve current coiled-coil stability prediction algorithms. Our findings enable tuning the stabilities of coiled-coil-based building modules match a diverse range of applications in synthetic biology and nanomaterials.

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 3%
Unknown 28 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 45%
Researcher 6 21%
Student > Bachelor 4 14%
Professor 2 7%
Student > Master 2 7%
Other 2 7%
Readers by discipline Count As %
Chemistry 15 52%
Biochemistry, Genetics and Molecular Biology 8 28%
Agricultural and Biological Sciences 3 10%
Unspecified 2 7%
Engineering 1 3%
Other 0 0%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 05 October 2017.
All research outputs
#1,577,580
of 8,617,648 outputs
Outputs from Journal of the American Chemical Society
#4,855
of 19,633 outputs
Outputs of similar age
#62,223
of 253,200 outputs
Outputs of similar age from Journal of the American Chemical Society
#129
of 270 outputs
Altmetric has tracked 8,617,648 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 19,633 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 75% 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 253,200 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 270 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.