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Insights to ligand binding to the monoamine transporters-from homology modeling to LeuBAT and dDAT.

Overview of attention for article published in Frontiers in Pharmacology, September 2015
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Title
Insights to ligand binding to the monoamine transporters-from homology modeling to LeuBAT and dDAT.
Published in
Frontiers in Pharmacology, September 2015
DOI 10.3389/fphar.2015.00208
Pubmed ID
Authors

Koldsø, Heidi, Grouleff, Julie, Schiøtt, Birgit

Abstract

Understanding of drug binding to the human biogenic amine transporters (BATs) is essential to explain the mechanism of action of these pharmaceuticals but more importantly to be able to develop new and improved compounds to be used in the treatment of depression or drug addiction. Until recently no high resolution structure was available of the BATs and homology modeling was a necessity. Various studies have revealed experimentally validated binding modes of numerous ligands to the BATs using homology modeling. Here we examine and discuss the similarities between the binding models of substrates, antidepressants, psychostimulants, and mazindol in homology models of the human BATs and the recently published crystal structures of the Drosophila dopamine transporter and the engineered protein, LeuBAT. The comparison reveals that careful computational modeling combined with experimental data can be utilized to predict binding of molecules to proteins that agree very well with crystal structures.

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

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 26%
Student > Bachelor 5 15%
Researcher 5 15%
Student > Master 5 15%
Student > Postgraduate 2 6%
Other 5 15%
Unknown 3 9%
Readers by discipline Count As %
Chemistry 9 26%
Biochemistry, Genetics and Molecular Biology 6 18%
Agricultural and Biological Sciences 6 18%
Pharmacology, Toxicology and Pharmaceutical Science 4 12%
Neuroscience 4 12%
Other 2 6%
Unknown 3 9%
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 07 October 2015.
All research outputs
#18,345,259
of 23,577,654 outputs
Outputs from Frontiers in Pharmacology
#7,528
of 17,181 outputs
Outputs of similar age
#186,948
of 275,989 outputs
Outputs of similar age from Frontiers in Pharmacology
#47
of 98 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 17,181 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one is in the 48th percentile – i.e., 48% 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 275,989 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 98 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.