↓ Skip to main content

An In-Silico Investigation of Key Lysine Residues and Their Selection for Clearing off Aβ and Holo-AβPP Through Ubiquitination

Overview of attention for article published in Interdisciplinary Sciences: Computational Life Sciences, September 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#13 of 297)
  • High Attention Score compared to outputs of the same age (80th percentile)

Mentioned by

news
1 news outlet
twitter
2 X users

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
11 Mendeley
Title
An In-Silico Investigation of Key Lysine Residues and Their Selection for Clearing off Aβ and Holo-AβPP Through Ubiquitination
Published in
Interdisciplinary Sciences: Computational Life Sciences, September 2018
DOI 10.1007/s12539-018-0307-2
Pubmed ID
Authors

Dhiraj Kumar, Pravir Kumar

Abstract

Malicious progression of neurodegeneration is a consequence of toxic aggregates of proteins or peptides such as amyloid beta (Aβ) reported in Alzheimer's disease (AD). These aggregates hinder the electrochemical transmission at neuronal junctions and thus deteriorate neuronal-health by triggering dementia. Electrostatic and hydrophobic interactions among amino-acid residues are the governing principle behind the self-assembly of aforesaid noxious oligomers or agglomerate. Interestingly, lysine residues are crucial for these interactions and for facilitating the clearance of toxic metabolites through the ubiquitination process. The mechanisms behind lysine selectivity and modifications of target proteins are very intriguing process and an avenue to explore the clearance of unwanted proteins from neurons. Therefore, it is fascinating for the researchers to investigate the role of key lysine, their selectivity and interactions with other amino acids to clear-off toxic products in exempting the progression of Neurodegenerative disorders (NDDs). Herein, (1) we identified the aggregation prone sequence in Aβ40 and Aβ42 as 'HHQKLVFFAE' and 'SGYEVHHQKLVFFAEDVG/KGAIIGLMVGGV' respectively with critical lysine (K) at 16 and 28 for stabilizing the aggregates; (2) elucidated the interaction pattern of AβPP with other Alzheimer's related proteins BACE1, APOE, SNCA, APBB1, CASP8, NAE1, ADAM10, and PSEN1 to describe the pathophysiology; (3) found APOE as commonly interacting factor between amyloid beta and Tau for governing AD pathogenesis; (4) reported K224, K351, K363, K377, K601, K662, K751, and K763 as potential putative lysine for facilitating AβPP clearance through ubiquitination thereby arresting Aβ formation; and (5) observed conserved glutamine (Q), glutamic acid (E), and alpha-helical conformation as few crucial factors for lysine selectivity in the ubiquitination of AβPP.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 27%
Unspecified 1 9%
Student > Bachelor 1 9%
Student > Ph. D. Student 1 9%
Researcher 1 9%
Other 2 18%
Unknown 2 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 18%
Unspecified 1 9%
Biochemistry, Genetics and Molecular Biology 1 9%
Nursing and Health Professions 1 9%
Medicine and Dentistry 1 9%
Other 2 18%
Unknown 3 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 14 September 2018.
All research outputs
#3,171,758
of 23,103,436 outputs
Outputs from Interdisciplinary Sciences: Computational Life Sciences
#13
of 297 outputs
Outputs of similar age
#66,142
of 336,158 outputs
Outputs of similar age from Interdisciplinary Sciences: Computational Life Sciences
#1
of 3 outputs
Altmetric has tracked 23,103,436 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 297 research outputs from this source. They receive a mean Attention Score of 2.8. This one has done particularly well, scoring higher than 94% 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 336,158 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them