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Rapid Profiling of Disease Alleles Using a Tunable Reporter of Protein Misfolding

Overview of attention for article published in Genetics, November 2012
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Title
Rapid Profiling of Disease Alleles Using a Tunable Reporter of Protein Misfolding
Published in
Genetics, November 2012
DOI 10.1534/genetics.112.143750
Pubmed ID
Authors

Adrianne M. C. Pittman, Melissa D. Lage, Vladimir Poltoratsky, Justin D. Vrana, Alessandro Paiardini, Alessandro Roncador, Barbara Cellini, Robert M. Hughes, Chandra L. Tucker

Abstract

Many human diseases are caused by genetic mutations that decrease protein stability. Such mutations may not specifically affect an active site, but can alter protein folding, abundance, or localization. Here we describe a high-throughput cell-based stability assay, IDESA (intra-DHFR enzyme stability assay), where stability is coupled to cell proliferation in the model yeast, Saccharomyces cerevisiae. The assay requires no prior knowledge of a protein's structure or activity, allowing the assessment of stability of proteins that have unknown or difficult to characterize activities, and we demonstrate use with a range of disease-relevant targets, including human alanine:glyoxylate aminotransferase (AGT), superoxide dismutase (SOD-1), DJ-1, p53, and SMN1. The assay can be carried out on hundreds of disease alleles in parallel or used to identify stabilizing small molecules (pharmacological chaperones) for unstable alleles. As demonstration of the general utility of this assay, we analyze stability of disease alleles of AGT, deficiency of which results in the kidney stone disease, primary hyperoxaluria type I, identifying mutations that specifically affect the protein-active site chemistry.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 2%
Unknown 44 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 29%
Researcher 12 27%
Professor 3 7%
Student > Doctoral Student 2 4%
Other 2 4%
Other 7 16%
Unknown 6 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 44%
Biochemistry, Genetics and Molecular Biology 11 24%
Medicine and Dentistry 4 9%
Chemistry 2 4%
Physics and Astronomy 1 2%
Other 2 4%
Unknown 5 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 15 November 2012.
All research outputs
#16,721,717
of 25,374,647 outputs
Outputs from Genetics
#5,921
of 7,400 outputs
Outputs of similar age
#129,620
of 202,252 outputs
Outputs of similar age from Genetics
#40
of 49 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one is in the 18th percentile – i.e., 18% 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 202,252 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.