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Predicting the mechanism of phospholipidosis

Overview of attention for article published in Journal of Cheminformatics, January 2012
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Average Attention Score compared to outputs of the same age and source

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3 X users

Citations

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82 Mendeley
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Title
Predicting the mechanism of phospholipidosis
Published in
Journal of Cheminformatics, January 2012
DOI 10.1186/1758-2946-4-2
Pubmed ID
Authors

Robert Lowe, Hamse Y Mussa, Florian Nigsch, Robert C Glen, John BO Mitchell

Abstract

The mechanism of phospholipidosis is still not well understood. Numerous different mechanisms have been proposed, varying from direct inhibition of the breakdown of phospholipids to the binding of a drug compound to the phospholipid, preventing breakdown. We have used a probabilistic method, the Parzen-Rosenblatt Window approach, to build a model from the ChEMBL dataset which can predict from a compound's structure both its primary pharmaceutical target and other targets with which it forms off-target, usually weaker, interactions. Using a small dataset of 182 phospholipidosis-inducing and non-inducing compounds, we predict their off-target activity against targets which could relate to phospholipidosis as a side-effect of a drug. We link these targets to specific mechanisms of inducing this lysosomal build-up of phospholipids in cells. Thus, we show that the induction of phospholipidosis is likely to occur by separate mechanisms when triggered by different cationic amphiphilic drugs. We find that both inhibition of phospholipase activity and enhanced cholesterol biosynthesis are likely to be important mechanisms. Furthermore, we provide evidence suggesting four specific protein targets. Sphingomyelin phosphodiesterase, phospholipase A2 and lysosomal phospholipase A1 are shown to be likely targets for the induction of phospholipidosis by inhibition of phospholipase activity, while lanosterol synthase is predicted to be associated with phospholipidosis being induced by enhanced cholesterol biosynthesis. This analysis provides the impetus for further experimental tests of these hypotheses.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 4%
Bulgaria 1 1%
Unknown 78 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 24%
Researcher 17 21%
Student > Master 10 12%
Student > Bachelor 10 12%
Other 3 4%
Other 10 12%
Unknown 12 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 20%
Chemistry 12 15%
Pharmacology, Toxicology and Pharmaceutical Science 9 11%
Computer Science 9 11%
Biochemistry, Genetics and Molecular Biology 6 7%
Other 13 16%
Unknown 17 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 03 April 2012.
All research outputs
#3,910,495
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#368
of 891 outputs
Outputs of similar age
#32,665
of 253,192 outputs
Outputs of similar age from Journal of Cheminformatics
#6
of 8 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has gotten more attention than average, scoring higher than 58% 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 253,192 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 87% 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 2 of them.