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Virtual Screening Against Carbohydrate-Binding Proteins: Evaluation and Application to Bacterial Burkholderia ambifaria Lectin

Overview of attention for article published in Journal of Chemical Information and Modeling, August 2018
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

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1 news outlet
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27 X users

Citations

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9 Dimensions

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30 Mendeley
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Title
Virtual Screening Against Carbohydrate-Binding Proteins: Evaluation and Application to Bacterial Burkholderia ambifaria Lectin
Published in
Journal of Chemical Information and Modeling, August 2018
DOI 10.1021/acs.jcim.8b00185
Pubmed ID
Authors

Tamir Dingjan, Émilie Gillon, Anne Imberty, Serge Pérez, Alexander Titz, Paul A. Ramsland, Elizabeth Yuriev

Abstract

Bacterial adhesion to human epithelia via lectins constitutes a therapeutic opportunity to prevent infection. Specifically, BambL (the lectin from Burkholderia ambifaria) is implicated in cystic fibrosis, where lectin-mediated bacterial adhesion to fucosylated lung epithelia is suspected to play an important role. We have employed structure-based virtual screening to identify inhibitors of BambL-saccharide interaction with potential therapeutic value. In order to enable such discovery, a virtual screening protocol has been iteratively developed via 194 retrospective screening protocols against four bacterial lectins (BambL, BC2L-A, FimH and LecA) with known ligands. Specific attention was given to the rigorous evaluation of retrospective screening, including calculation of analytical errors for enrichment metrics. The developed virtual screening workflow used crystallographic constraints, pharmacophore filters, and a final manual selection step. The protocol was applied to BambL, predicting 15 active compounds from virtual libraries of approximately 7 million compounds. Experimental validation using fluorescence polarization confirmed micromolar inhibitory activity for two compounds, which were further characterized by isothermal titration calorimetry and surface plasmon resonance. Subsequent testing against LecB from Pseudomonas aeruginosa demonstrated binding specificity of one of the hit compounds. This report demonstrates the utility of virtual screening protocols, integrating ligand-based pharmacophore filtering and structure-based constraints, in the search for bacterial lectin inhibitors.

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The data shown below were collected from the profiles of 27 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 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 20%
Researcher 6 20%
Student > Bachelor 2 7%
Librarian 2 7%
Professor > Associate Professor 2 7%
Other 6 20%
Unknown 6 20%
Readers by discipline Count As %
Chemistry 7 23%
Biochemistry, Genetics and Molecular Biology 4 13%
Pharmacology, Toxicology and Pharmaceutical Science 2 7%
Immunology and Microbiology 2 7%
Nursing and Health Professions 1 3%
Other 5 17%
Unknown 9 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 04 April 2019.
All research outputs
#1,578,428
of 25,452,734 outputs
Outputs from Journal of Chemical Information and Modeling
#1
of 1 outputs
Outputs of similar age
#32,294
of 341,812 outputs
Outputs of similar age from Journal of Chemical Information and Modeling
#3
of 72 outputs
Altmetric has tracked 25,452,734 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 0.0. This one scored the same or higher as 0 of them.
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 341,812 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 72 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.