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Precision is essential for efficient catalysis in an evolved Kemp eliminase

Overview of attention for article published in Nature, October 2013
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • Average Attention Score compared to outputs of the same age and source

Citations

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387 Mendeley
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1 CiteULike
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Title
Precision is essential for efficient catalysis in an evolved Kemp eliminase
Published in
Nature, October 2013
DOI 10.1038/nature12623
Pubmed ID
Authors

Rebecca Blomberg, Hajo Kries, Daniel M. Pinkas, Peer R. E. Mittl, Markus G. Grütter, Heidi K. Privett, Stephen L. Mayo, Donald Hilvert

Abstract

Linus Pauling established the conceptual framework for understanding and mimicking enzymes more than six decades ago. The notion that enzymes selectively stabilize the rate-limiting transition state of the catalysed reaction relative to the bound ground state reduces the problem of design to one of molecular recognition. Nevertheless, past attempts to capitalize on this idea, for example by using transition state analogues to elicit antibodies with catalytic activities, have generally failed to deliver true enzymatic rates. The advent of computational design approaches, combined with directed evolution, has provided an opportunity to revisit this problem. Starting from a computationally designed catalyst for the Kemp elimination--a well-studied model system for proton transfer from carbon--we show that an artificial enzyme can be evolved that accelerates an elementary chemical reaction 6 × 10(8)-fold, approaching the exceptional efficiency of highly optimized natural enzymes such as triosephosphate isomerase. A 1.09 Å resolution crystal structure of the evolved enzyme indicates that familiar catalytic strategies such as shape complementarity and precisely placed catalytic groups can be successfully harnessed to afford such high rate accelerations, making us optimistic about the prospects of designing more sophisticated catalysts.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 387 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 2%
United Kingdom 3 <1%
Japan 2 <1%
Ireland 1 <1%
Australia 1 <1%
Switzerland 1 <1%
France 1 <1%
Israel 1 <1%
Spain 1 <1%
Other 0 0%
Unknown 369 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 121 31%
Researcher 69 18%
Student > Bachelor 40 10%
Student > Master 35 9%
Student > Doctoral Student 15 4%
Other 39 10%
Unknown 68 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 96 25%
Chemistry 92 24%
Agricultural and Biological Sciences 90 23%
Engineering 10 3%
Computer Science 8 2%
Other 17 4%
Unknown 74 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 06 October 2022.
All research outputs
#1,926,364
of 24,162,843 outputs
Outputs from Nature
#41,324
of 94,370 outputs
Outputs of similar age
#17,804
of 215,608 outputs
Outputs of similar age from Nature
#647
of 1,060 outputs
Altmetric has tracked 24,162,843 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 94,370 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 101.4. This one has gotten more attention than average, scoring higher than 56% 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 215,608 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 91% of its contemporaries.
We're also able to compare this research output to 1,060 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.