↓ Skip to main content

Identification and characterization of Aβ peptide interactors in Alzheimer’s disease by structural approaches

Overview of attention for article published in Frontiers in Aging Neuroscience, October 2014
Altmetric Badge

Mentioned by

twitter
1 X user

Readers on

mendeley
35 Mendeley
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
Identification and characterization of Aβ peptide interactors in Alzheimer’s disease by structural approaches
Published in
Frontiers in Aging Neuroscience, October 2014
DOI 10.3389/fnagi.2014.00265
Pubmed ID
Authors

Keith D. Philibert, Robert A. Marr, Eric M. Norstrom, Marc J. Glucksman

Abstract

Currently, there are very limited pharmaceutical interventions for Alzheimer's disease (AD) to alleviate the amyloid burden implicated in the pathophysiology of the disease. Alzheimer's disease is characterized immunohistologically by the accumulation of senile plaques in the brain with afflicted patients progressively losing short-term memory and, ultimately, cognition. Although significant improvements in clinical diagnosis and care for AD patients have been made, effective treatments for this devastating disease remain elusive. A key component of the amyloid burden of AD comes from accumulation of the amyloid-beta (Aβ) peptide which comes from processing of the amyloid precursor protein (APP) by enzymes termed secretases, leading to production of these toxic Aβ peptides of 40-42 amino acids. New therapeutic approaches for reducing Aβ are warranted after the most logical avenues of inhibiting secretase activity appear less than optimal in ameliorating the progression of AD.Novel therapeutics may be gleaned from proteomics biomarker initiatives to yield detailed molecular interactions of enzymes and their potential substrates. Explicating the APPome by deciphering protein complexes forming in cells is a complementary approach to unveil novel molecular interactions with the amyloidogenic peptide precursor to both understand the biology and develop potential upstream drug targets. Utilizing these strategies we have identified EC 3.4.24.15 (EP24.15), a zinc metalloprotease related to neprilysin (NEP), with the ability to catabolize Aβ 1-42 by examining first potential in silico docking and then verification by mass spectrometry. In addition, a hormone carrier protein, transthyreitin (TTR), was identified and with its abundance in cerebrospinal fluid (CSF), found to clear Aβ by inhibiting formation of oligomeric forms of Aβ peptide. The confluence of complementary strategies may allow new therapeutic avenues as well as biomarkers for AD that will aid in diagnosis, prognosis and treatment.

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

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 17%
Student > Bachelor 5 14%
Student > Master 5 14%
Other 4 11%
Student > Doctoral Student 3 9%
Other 6 17%
Unknown 6 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 14%
Agricultural and Biological Sciences 5 14%
Medicine and Dentistry 4 11%
Neuroscience 4 11%
Pharmacology, Toxicology and Pharmaceutical Science 3 9%
Other 7 20%
Unknown 7 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 11 November 2014.
All research outputs
#20,242,779
of 22,770,070 outputs
Outputs from Frontiers in Aging Neuroscience
#4,273
of 4,754 outputs
Outputs of similar age
#213,161
of 255,206 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#71
of 83 outputs
Altmetric has tracked 22,770,070 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,754 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one is in the 1st percentile – i.e., 1% 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 255,206 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 83 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.