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The polypharmacology browser: a web-based multi-fingerprint target prediction tool using ChEMBL bioactivity data

Overview of attention for article published in Journal of Cheminformatics, February 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Average Attention Score compared to outputs of the same age and source

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11 X users
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1 Google+ user

Citations

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116 Mendeley
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Title
The polypharmacology browser: a web-based multi-fingerprint target prediction tool using ChEMBL bioactivity data
Published in
Journal of Cheminformatics, February 2017
DOI 10.1186/s13321-017-0199-x
Pubmed ID
Authors

Mahendra Awale, Jean-Louis Reymond

Abstract

Several web-based tools have been reported recently which predict the possible targets of a small molecule by similarity to compounds of known bioactivity using molecular fingerprints (fps), however predictions in each case rely on similarities computed from only one or two fps. Considering that structural similarity and therefore the predicted targets strongly depend on the method used for comparison, it would be highly desirable to predict targets using a broader set of fps simultaneously. Herein, we present the polypharmacology browser (PPB), a web-based platform which predicts possible targets for small molecules by searching for nearest neighbors using ten different fps describing composition, substructures, molecular shape and pharmacophores. PPB searches through 4613 groups of at least 10 same target annotated bioactive molecules from ChEMBL and returns a list of predicted targets ranked by consensus voting scheme and p value. A validation study across 670 drugs with up to 20 targets showed that combining the predictions from all 10 fps gives the best results, with on average 50% of the known targets of a drug being correctly predicted with a hit rate of 25%. Furthermore, when profiling a new inhibitor of the calcium channel TRPV6 against 24 targets taken from a safety screen panel, we observed inhibition in 5 out of 5 targets predicted by PPB and in 7 out of 18 targets not predicted by PPB. The rate of correct (5/12) and incorrect (0/12) predictions for this compound by PPB was comparable to that of other web-based prediction tools. PPB offers a versatile platform for target prediction based on multi-fingerprint comparisons, and is freely accessible at www.gdb.unibe.ch as a valuable support for drug discovery.Graphical abstract.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 2%
Spain 1 <1%
Brazil 1 <1%
Unknown 112 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 19%
Researcher 22 19%
Student > Master 14 12%
Student > Bachelor 14 12%
Other 8 7%
Other 15 13%
Unknown 21 18%
Readers by discipline Count As %
Chemistry 25 22%
Pharmacology, Toxicology and Pharmaceutical Science 17 15%
Agricultural and Biological Sciences 12 10%
Biochemistry, Genetics and Molecular Biology 11 9%
Computer Science 10 9%
Other 15 13%
Unknown 26 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 2019.
All research outputs
#4,726,618
of 24,998,746 outputs
Outputs from Journal of Cheminformatics
#433
of 938 outputs
Outputs of similar age
#77,897
of 316,413 outputs
Outputs of similar age from Journal of Cheminformatics
#11
of 20 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 938 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has gotten more attention than average, scoring higher than 53% 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 316,413 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 75% of its contemporaries.
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 has gotten more attention than average, scoring higher than 50% of its contemporaries.