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Accurate de novo design of hyperstable constrained peptides

Overview of attention for article published in Nature, September 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

news
12 news outlets
blogs
2 blogs
twitter
100 X users
patent
7 patents
facebook
3 Facebook pages

Citations

dimensions_citation
333 Dimensions

Readers on

mendeley
826 Mendeley
citeulike
6 CiteULike
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Title
Accurate de novo design of hyperstable constrained peptides
Published in
Nature, September 2016
DOI 10.1038/nature19791
Pubmed ID
Authors

Gaurav Bhardwaj, Vikram Khipple Mulligan, Christopher D. Bahl, Jason M. Gilmore, Peta J. Harvey, Olivier Cheneval, Garry W. Buchko, Surya V. S. R. K. Pulavarti, Quentin Kaas, Alexander Eletsky, Po-Ssu Huang, William A. Johnsen, Per Jr Greisen, Gabriel J. Rocklin, Yifan Song, Thomas W. Linsky, Andrew Watkins, Stephen A. Rettie, Xianzhong Xu, Lauren P. Carter, Richard Bonneau, James M. Olson, Evangelos Coutsias, Colin E. Correnti, Thomas Szyperski, David J. Craik, David Baker

Abstract

Naturally occurring, pharmacologically active peptides constrained with covalent crosslinks generally have shapes that have evolved to fit precisely into binding pockets on their targets. Such peptides can have excellent pharmaceutical properties, combining the stability and tissue penetration of small-molecule drugs with the specificity of much larger protein therapeutics. The ability to design constrained peptides with precisely specified tertiary structures would enable the design of shape-complementary inhibitors of arbitrary targets. Here we describe the development of computational methods for accurate de novo design of conformationally restricted peptides, and the use of these methods to design 18-47 residue, disulfide-crosslinked peptides, a subset of which are heterochiral and/or N-C backbone-cyclized. Both genetically encodable and non-canonical peptides are exceptionally stable to thermal and chemical denaturation, and 12 experimentally determined X-ray and NMR structures are nearly identical to the computational design models. The computational design methods and stable scaffolds presented here provide the basis for development of a new generation of peptide-based drugs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 100 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 826 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 1%
United Kingdom 5 <1%
Japan 2 <1%
Italy 1 <1%
Brazil 1 <1%
France 1 <1%
Switzerland 1 <1%
Germany 1 <1%
India 1 <1%
Other 1 <1%
Unknown 803 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 237 29%
Researcher 161 19%
Student > Bachelor 82 10%
Student > Master 79 10%
Student > Doctoral Student 37 4%
Other 113 14%
Unknown 117 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 202 24%
Chemistry 187 23%
Agricultural and Biological Sciences 136 16%
Computer Science 33 4%
Engineering 30 4%
Other 99 12%
Unknown 139 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 161. 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 30 November 2023.
All research outputs
#258,585
of 25,734,859 outputs
Outputs from Nature
#14,574
of 98,631 outputs
Outputs of similar age
#4,918
of 331,629 outputs
Outputs of similar age from Nature
#286
of 999 outputs
Altmetric has tracked 25,734,859 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 98,631 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 102.6. This one has done well, scoring higher than 85% 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 331,629 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 999 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 71% of its contemporaries.