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Directed evolution of artificial metalloenzymes for in vivo metathesis

Overview of attention for article published in Nature, August 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 (74th percentile)

Mentioned by

news
18 news outlets
blogs
4 blogs
twitter
55 X users
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2 patents
googleplus
3 Google+ users
f1000
1 research highlight platform

Citations

dimensions_citation
371 Dimensions

Readers on

mendeley
619 Mendeley
citeulike
2 CiteULike
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Title
Directed evolution of artificial metalloenzymes for in vivo metathesis
Published in
Nature, August 2016
DOI 10.1038/nature19114
Pubmed ID
Authors

Markus Jeschek, Raphael Reuter, Tillmann Heinisch, Christian Trindler, Juliane Klehr, Sven Panke, Thomas R. Ward

Abstract

The field of biocatalysis has advanced from harnessing natural enzymes to using directed evolution to obtain new biocatalysts with tailor-made functions. Several tools have recently been developed to expand the natural enzymatic repertoire with abiotic reactions. For example, artificial metalloenzymes, which combine the versatile reaction scope of transition metals with the beneficial catalytic features of enzymes, offer an attractive means to engineer new reactions. Three complementary strategies exist: repurposing natural metalloenzymes for abiotic transformations; in silico metalloenzyme (re-)design; and incorporation of abiotic cofactors into proteins. The third strategy offers the opportunity to design a wide variety of artificial metalloenzymes for non-natural reactions. However, many metal cofactors are inhibited by cellular components and therefore require purification of the scaffold protein. This limits the throughput of genetic optimization schemes applied to artificial metalloenzymes and their applicability in vivo to expand natural metabolism. Here we report the compartmentalization and in vivo evolution of an artificial metalloenzyme for olefin metathesis, which represents an archetypal organometallic reaction without equivalent in nature. Building on previous work on an artificial metallohydrolase, we exploit the periplasm of Escherichia coli as a reaction compartment for the 'metathase' because it offers an auspicious environment for artificial metalloenzymes, mainly owing to low concentrations of inhibitors such as glutathione, which has recently been identified as a major inhibitor. This strategy facilitated the assembly of a functional metathase in vivo and its directed evolution with substantially increased throughput compared to conventional approaches that rely on purified protein variants. The evolved metathase compares favourably with commercial catalysts, shows activity for different metathesis substrates and can be further evolved in different directions by adjusting the workflow. Our results represent the systematic implementation and evolution of an artificial metalloenzyme that catalyses an abiotic reaction in vivo, with potential applications in, for example, non-natural metabolism.

X Demographics

X Demographics

The data shown below were collected from the profiles of 55 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 619 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 <1%
Germany 1 <1%
Hungary 1 <1%
Finland 1 <1%
Netherlands 1 <1%
Unknown 609 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 186 30%
Researcher 92 15%
Student > Bachelor 72 12%
Student > Master 64 10%
Student > Doctoral Student 27 4%
Other 76 12%
Unknown 102 16%
Readers by discipline Count As %
Chemistry 278 45%
Biochemistry, Genetics and Molecular Biology 105 17%
Agricultural and Biological Sciences 74 12%
Chemical Engineering 16 3%
Engineering 12 2%
Other 21 3%
Unknown 113 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 195. 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 27 July 2022.
All research outputs
#208,008
of 25,839,971 outputs
Outputs from Nature
#12,282
of 98,905 outputs
Outputs of similar age
#4,032
of 350,555 outputs
Outputs of similar age from Nature
#247
of 984 outputs
Altmetric has tracked 25,839,971 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 98,905 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 102.7. 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 350,555 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 984 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 74% of its contemporaries.