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Find novel dual-agonist drugs for treating type 2 diabetes by means of cheminformatics

Overview of attention for article published in Drug Design, Development and Therapy, April 2013
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1 X user
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1 Facebook page

Citations

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35 Dimensions

Readers on

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49 Mendeley
Title
Find novel dual-agonist drugs for treating type 2 diabetes by means of cheminformatics
Published in
Drug Design, Development and Therapy, April 2013
DOI 10.2147/dddt.s42113
Pubmed ID
Authors

Lei Liu, Ying Ma, Run-Ling Wang, Wei-Ren Xu, Shu-Qing Wang, Kuo-Chen Chou

Abstract

The high prevalence of type 2 diabetes mellitus in the world as well as the increasing reports about the adverse side effects of the existing diabetes treatment drugs have made developing new and effective drugs against the disease a very high priority. In this study, we report ten novel compounds found by targeting peroxisome proliferator-activated receptors (PPARs) using virtual screening and core hopping approaches. PPARs have drawn increasing attention for developing novel drugs to treat diabetes due to their unique functions in regulating glucose, lipid, and cholesterol metabolism. The reported compounds are featured with dual functions, and hence belong to the category of dual agonists. Compared with the single PPAR agonists, the dual PPAR agonists, formed by combining the lipid benefit of PPARα agonists (such as fibrates) and the glycemic advantages of the PPARγ agonists (such as thiazolidinediones), are much more powerful in treating diabetes because they can enhance metabolic effects while minimizing the side effects. This was observed in the studies on molecular dynamics simulations, as well as on absorption, distribution, metabolism, and excretion, that these novel dual agonists not only possessed the same function as ragaglitazar (an investigational drug developed by Novo Nordisk for treating type 2 diabetes) did in activating PPARα and PPARγ, but they also had more favorable conformation for binding to the two receptors. Moreover, the residues involved in forming the binding pockets of PPARα and PPARγ among the top ten compounds are explicitly presented, and this will be very useful for the in-depth conduction of mutagenesis experiments. It is anticipated that the ten compounds may become potential drug candidates, or at the very least, the findings reported here may stimulate new strategies or provide useful insights for designing new and more powerful dual-agonist drugs for treating type 2 diabetes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 2%
India 1 2%
Unknown 47 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 16%
Unspecified 7 14%
Student > Ph. D. Student 6 12%
Student > Bachelor 6 12%
Student > Doctoral Student 5 10%
Other 13 27%
Unknown 4 8%
Readers by discipline Count As %
Chemistry 10 20%
Medicine and Dentistry 9 18%
Unspecified 7 14%
Pharmacology, Toxicology and Pharmaceutical Science 6 12%
Agricultural and Biological Sciences 5 10%
Other 7 14%
Unknown 5 10%
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 16 April 2013.
All research outputs
#16,978,129
of 25,728,855 outputs
Outputs from Drug Design, Development and Therapy
#1,027
of 2,280 outputs
Outputs of similar age
#132,841
of 213,894 outputs
Outputs of similar age from Drug Design, Development and Therapy
#12
of 20 outputs
Altmetric has tracked 25,728,855 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,280 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has gotten more attention than average, scoring higher than 50% 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 213,894 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.