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Computer-Aided Drug Design in Epigenetics

Overview of attention for article published in Frontiers in Chemistry, March 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

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2 X users

Citations

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166 Mendeley
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Title
Computer-Aided Drug Design in Epigenetics
Published in
Frontiers in Chemistry, March 2018
DOI 10.3389/fchem.2018.00057
Pubmed ID
Authors

Wenchao Lu, Rukang Zhang, Hao Jiang, Huimin Zhang, Cheng Luo

Abstract

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation, and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field.

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

Geographical breakdown

Country Count As %
Unknown 166 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 15%
Student > Master 23 14%
Student > Bachelor 17 10%
Student > Doctoral Student 16 10%
Researcher 14 8%
Other 24 14%
Unknown 47 28%
Readers by discipline Count As %
Chemistry 33 20%
Biochemistry, Genetics and Molecular Biology 29 17%
Pharmacology, Toxicology and Pharmaceutical Science 18 11%
Agricultural and Biological Sciences 7 4%
Computer Science 5 3%
Other 17 10%
Unknown 57 34%
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 08 April 2018.
All research outputs
#18,590,133
of 23,026,672 outputs
Outputs from Frontiers in Chemistry
#2,227
of 6,010 outputs
Outputs of similar age
#258,583
of 332,696 outputs
Outputs of similar age from Frontiers in Chemistry
#54
of 127 outputs
Altmetric has tracked 23,026,672 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,010 research outputs from this source. They receive a mean Attention Score of 2.0. This one has gotten more attention than average, scoring higher than 51% 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 332,696 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 127 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 54% of its contemporaries.