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A fast topological analysis algorithm for large-scale similarity evaluations of ligands and binding pockets

Overview of attention for article published in Journal of Cheminformatics, August 2015
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Mentioned by

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2 tweeters

Citations

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2 Dimensions

Readers on

mendeley
35 Mendeley
Title
A fast topological analysis algorithm for large-scale similarity evaluations of ligands and binding pockets
Published in
Journal of Cheminformatics, August 2015
DOI 10.1186/s13321-015-0091-5
Pubmed ID
Authors

Mohammad ElGamacy, Luc Van Meervelt

Abstract

With the rapid increase of the structural data of biomolecular complexes, novel structural analysis methods have to be devised with high-throughput capacity to handle immense data input and to construct massive networks at the minimal computational cost. Moreover, novel methods should be capable of handling a broad range of molecular structural sizes and chemical natures, cognisant of the conformational and electrostatic bases of molecular recognition, and sufficiently accurate to enable contextually relevant biological inferences. A novel molecular topology comparison method was developed and tested. The method was tested for both ligand and binding pocket similarity analyses and a PDB-wide ligand topological similarity map was computed. The unprecedentedly wide scope of ligand definition and large-scale topological similarity mapping can provide very robust tools, of performance unmatched by the present alignment-based methods. The method remarkably shows potential for application for scaffold hopping purposes. It also opens new frontiers in the areas of ligand-mediated protein connectivity, ligand-based molecular phylogeny, target fishing, and off-target predictions. Graphical abstract:A novel molecular topology comparison method based on a combined shape distribution and charge binning scheme is presented.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 20%
Researcher 7 20%
Student > Master 6 17%
Student > Bachelor 4 11%
Professor > Associate Professor 3 9%
Other 5 14%
Unknown 3 9%
Readers by discipline Count As %
Chemistry 12 34%
Agricultural and Biological Sciences 8 23%
Computer Science 8 23%
Biochemistry, Genetics and Molecular Biology 2 6%
Engineering 2 6%
Other 0 0%
Unknown 3 9%

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 02 September 2015.
All research outputs
#9,231,039
of 12,010,397 outputs
Outputs from Journal of Cheminformatics
#421
of 467 outputs
Outputs of similar age
#152,321
of 238,985 outputs
Outputs of similar age from Journal of Cheminformatics
#11
of 11 outputs
Altmetric has tracked 12,010,397 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 467 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.9. This one is in the 7th percentile – i.e., 7% 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 238,985 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.