↓ Skip to main content

Prediction of Anti-Alzheimer's Activity of Flavonoids Targeting Acetylcholinesterase in silico

Overview of attention for article published in Phytochemical Analysis, February 2017
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#4 of 304)
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
1 tweeter

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
38 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
Prediction of Anti-Alzheimer's Activity of Flavonoids Targeting Acetylcholinesterase in silico
Published in
Phytochemical Analysis, February 2017
DOI 10.1002/pca.2679
Pubmed ID
Authors

Subrata Das, Monjur A. Laskar, Satyajit D. Sarker, Manabendra D. Choudhury, Prakash Roy Choudhury, Abhijit Mitra, Shajarahtunnur Jamil, Siti Mariam A. Lathiff, Siti Awanis Abdullah, Norazah Basar, Lutfun Nahar, Anupam D. Talukdar

Abstract

Prenylated and pyrano-flavonoids of the genus Artocarpus J. R. Forster & G. Forster are well known for their acetylcholinesterase (AChE) inhibitory, anti-cholinergic, anti-inflammatory, anti-microbial, anti-oxidant, anti-proliferative and tyrosinase inhibitory activities. Some of these compounds have also been shown to be effective against Alzheimer's disease. The aim of the in silico study was to establish protocols to predict the most effective flavonoid from prenylated and pyrano-flavonoid classes for AChE inhibition linking to the potential treatment of Alzheimer's disease. Three flavonoids isolated from Artocarpus anisophyllus Miq. were selected for the study. With these compounds, Lipinski filter, ADME/Tox screening, molecular docking and quantitative structure-activity relationship (QSAR) were performed in silico. In vitro activity was evaluated by bioactivity staining based on the Ellman's method. In the Lipinski filter and ADME/Tox screening, all test compounds produced positive results, but in the target fishing, only one flavonoid could successfully target AChE. Molecular docking was performed on this flavonoid, and this compound gained the score as -13.5762. From the QSAR analysis the IC50 was found to be 1659.59 nM. Again, 100 derivatives were generated from the parent compound and docking was performed. The derivative compound 20 was the best scorer, i.e. -31.6392 and IC50 was predicted as 6.025 nM. Results indicated that flavonoids could be efficient inhibitors of AChE and thus, could be useful in the management of Alzheimer's disease. Copyright © 2017 John Wiley & Sons, Ltd.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Pakistan 1 3%
Unknown 37 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 16%
Student > Master 5 13%
Student > Bachelor 4 11%
Lecturer > Senior Lecturer 3 8%
Student > Doctoral Student 3 8%
Other 9 24%
Unknown 8 21%
Readers by discipline Count As %
Chemistry 10 26%
Medicine and Dentistry 5 13%
Biochemistry, Genetics and Molecular Biology 3 8%
Psychology 3 8%
Computer Science 2 5%
Other 4 11%
Unknown 11 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 09 May 2017.
All research outputs
#866,972
of 12,184,227 outputs
Outputs from Phytochemical Analysis
#4
of 304 outputs
Outputs of similar age
#37,931
of 330,924 outputs
Outputs of similar age from Phytochemical Analysis
#1
of 8 outputs
Altmetric has tracked 12,184,227 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 304 research outputs from this source. They receive a mean Attention Score of 2.9. This one has done particularly well, scoring higher than 98% 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 330,924 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 88% of its contemporaries.
We're also able to compare this research output to 8 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