↓ Skip to main content

Massively parallel de novo protein design for targeted therapeutics

Overview of attention for article published in Nature, September 2017
Altmetric Badge

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 (73rd percentile)

Mentioned by

news
13 news outlets
blogs
4 blogs
twitter
130 X users
patent
23 patents
facebook
1 Facebook page
video
2 YouTube creators

Citations

dimensions_citation
354 Dimensions

Readers on

mendeley
968 Mendeley
citeulike
6 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Massively parallel de novo protein design for targeted therapeutics
Published in
Nature, September 2017
DOI 10.1038/nature23912
Pubmed ID
Authors

Aaron Chevalier, Daniel-Adriano Silva, Gabriel J. Rocklin, Derrick R. Hicks, Renan Vergara, Patience Murapa, Steffen M. Bernard, Lu Zhang, Kwok-Ho Lam, Guorui Yao, Christopher D. Bahl, Shin-Ichiro Miyashita, Inna Goreshnik, James T. Fuller, Merika T. Koday, Cody M. Jenkins, Tom Colvin, Lauren Carter, Alan Bohn, Cassie M. Bryan, D. Alejandro Fernández-Velasco, Lance Stewart, Min Dong, Xuhui Huang, Rongsheng Jin, Ian A. Wilson, Deborah H. Fuller, David Baker

Abstract

De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37-43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.

X Demographics

X Demographics

The data shown below were collected from the profiles of 130 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 968 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 968 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 240 25%
Researcher 186 19%
Student > Master 91 9%
Student > Bachelor 90 9%
Student > Doctoral Student 48 5%
Other 133 14%
Unknown 180 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 289 30%
Agricultural and Biological Sciences 174 18%
Chemistry 121 13%
Engineering 39 4%
Chemical Engineering 26 3%
Other 120 12%
Unknown 199 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 192. 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 09 January 2024.
All research outputs
#207,953
of 25,525,181 outputs
Outputs from Nature
#12,310
of 98,145 outputs
Outputs of similar age
#4,309
of 328,949 outputs
Outputs of similar age from Nature
#252
of 955 outputs
Altmetric has tracked 25,525,181 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 98,145 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 87% 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 328,949 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 955 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 73% of its contemporaries.