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Cleavage Entropy as Quantitative Measure of Protease Specificity

Overview of attention for article published in PLoS Computational Biology, April 2013
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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1 X user
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1 Wikipedia page

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63 Mendeley
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1 CiteULike
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Title
Cleavage Entropy as Quantitative Measure of Protease Specificity
Published in
PLoS Computational Biology, April 2013
DOI 10.1371/journal.pcbi.1003007
Pubmed ID
Authors

Julian E. Fuchs, Susanne von Grafenstein, Roland G. Huber, Michael A. Margreiter, Gudrun M. Spitzer, Hannes G. Wallnoefer, Klaus R. Liedl

Abstract

A purely information theory-guided approach to quantitatively characterize protease specificity is established. We calculate an entropy value for each protease subpocket based on sequences of cleaved substrates extracted from the MEROPS database. We compare our results with known subpocket specificity profiles for individual proteases and protease groups (e.g. serine proteases, metallo proteases) and reflect them quantitatively. Summation of subpocket-wise cleavage entropy contributions yields a measure for overall protease substrate specificity. This total cleavage entropy allows ranking of different proteases with respect to their specificity, separating unspecific digestive enzymes showing high total cleavage entropy from specific proteases involved in signaling cascades. The development of a quantitative cleavage entropy score allows an unbiased comparison of subpocket-wise and overall protease specificity. Thus, it enables assessment of relative importance of physicochemical and structural descriptors in protease recognition. We present an exemplary application of cleavage entropy in tracing substrate specificity in protease evolution. This highlights the wide range of substrate promiscuity within homologue proteases and hence the heavy impact of a limited number of mutations on individual substrate specificity.

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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Australia 1 2%
Brazil 1 2%
Unknown 60 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 24%
Researcher 9 14%
Student > Bachelor 7 11%
Student > Master 7 11%
Student > Doctoral Student 5 8%
Other 11 17%
Unknown 9 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 30%
Chemistry 13 21%
Biochemistry, Genetics and Molecular Biology 12 19%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Computer Science 2 3%
Other 4 6%
Unknown 11 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 September 2022.
All research outputs
#7,543,239
of 25,891,484 outputs
Outputs from PLoS Computational Biology
#5,063
of 9,065 outputs
Outputs of similar age
#59,978
of 211,335 outputs
Outputs of similar age from PLoS Computational Biology
#61
of 146 outputs
Altmetric has tracked 25,891,484 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 9,065 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.3. This one is in the 42nd percentile – i.e., 42% 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 211,335 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 146 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 56% of its contemporaries.