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Mentioned by

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2 X users

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mendeley
25 Mendeley
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Article details
Title
Systematic study of the structural parameters affecting the self-assembly of cyclic peptide–poly(ethylene glycol) conjugates
Published in
Soft Matter, January 2018
DOI 10.1039/c8sm01133h
Pubmed ID
Authors
Abstract

Self-assembling cyclic peptides (CP) consisting of amino acids with alternating d- and l-chirality form nanotubes by hydrogen bonding, hydrophobic interactions, and π-π stacking in solution. These highly dynamic materials are emerging as promising supramolecular systems for a wide range of biomedical applications. Herein, we discuss how varying the polymer conformation (linear vs. brush), as well as the number of polymer arms per peptide unimer affects the self-assembly of PEGylated cyclic peptides in different solvents, using small angle neutron scattering. Using the derived information, strong correlations were drawn between the size of the aggregates, solvent polarity, and its ability to compete for hydrogen bonding interactions between the peptide unimers. Using these data, it could be possible to engineer cyclic peptide nanotubes of a controlled length.

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Timeline Attention over time Attention Score history
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X Demographics

X Demographics

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 demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 5 20%
Student > Ph. D. Student 4 16%
Student > Bachelor 2 8%
Student > Master 2 8%
Student > Doctoral Student 1 4%
Other 1 4%
Unknown 10 40%
Readers by discipline
Readers by discipline Count As %
Chemistry 11 44%
Materials Science 2 8%
Energy 1 4%
Engineering 1 4%
Unknown 10 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 08 July 2019.
All research outputs
#23,562,104
of 33,176,665 outputs
Outputs from Soft Matter
#5,500
of 10,061 outputs
Outputs of similar age
#327,769
of 486,030 outputs
Outputs of similar age from Soft Matter
#424
of 988 outputs
Altmetric has tracked 33,176,665 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,061 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 35th percentile – i.e., 35% of its peers scored the same or lower than it.
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 486,030 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 988 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.