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Prediction of the P. falciparum Target Space Relevant to Malaria Drug Discovery

Overview of attention for article published in PLoS Computational Biology, October 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

blogs
1 blog
twitter
3 X users
facebook
1 Facebook page
googleplus
1 Google+ user
f1000
1 research highlight platform

Citations

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36 Dimensions

Readers on

mendeley
129 Mendeley
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3 CiteULike
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Title
Prediction of the P. falciparum Target Space Relevant to Malaria Drug Discovery
Published in
PLoS Computational Biology, October 2013
DOI 10.1371/journal.pcbi.1003257
Pubmed ID
Authors

Andreas Spitzmüller, Jordi Mestres

Abstract

Malaria is still one of the most devastating infectious diseases, affecting hundreds of millions of patients worldwide. Even though there are several established drugs in clinical use for malaria treatment, there is an urgent need for new drugs acting through novel mechanisms of action due to the rapid development of resistance. Resistance emerges when the parasite manages to mutate the sequence of the drug targets to the extent that the protein can still perform its function in the parasite but can no longer be inhibited by the drug, which then becomes almost ineffective. The design of a new generation of malaria drugs targeting multiple essential proteins would make it more difficult for the parasite to develop full resistance without lethally disrupting some of its vital functions. The challenge is then to identify which set of Plasmodium falciparum proteins, among the millions of possible combinations, can be targeted at the same time by a given chemotype. To do that, we predicted first the targets of the close to 20,000 antimalarial hits identified recently in three independent phenotypic screening campaigns. All targets predicted were then projected onto the genome of P. falciparum using orthologous relationships. A total of 226 P. falciparum proteins were predicted to be hit by at least one compound, of which 39 were found to be significantly enriched by the presence and degree of affinity of phenotypically active compounds. The analysis of the chemically compatible target combinations containing at least one of those 39 targets led to the identification of a priority set of 64 multi-target profiles that can set the ground for a new generation of more robust malaria drugs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 4 3%
India 3 2%
Brazil 2 2%
Germany 1 <1%
Peru 1 <1%
Spain 1 <1%
Unknown 117 91%

Demographic breakdown

Readers by professional status Count As %
Student > Master 24 19%
Researcher 23 18%
Student > Ph. D. Student 21 16%
Student > Bachelor 16 12%
Student > Postgraduate 10 8%
Other 21 16%
Unknown 14 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 26%
Chemistry 23 18%
Biochemistry, Genetics and Molecular Biology 16 12%
Pharmacology, Toxicology and Pharmaceutical Science 9 7%
Medicine and Dentistry 8 6%
Other 18 14%
Unknown 21 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 26 July 2019.
All research outputs
#3,215,397
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#2,841
of 8,964 outputs
Outputs of similar age
#28,831
of 224,633 outputs
Outputs of similar age from PLoS Computational Biology
#41
of 133 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,964 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has gotten more attention than average, scoring higher than 68% 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 224,633 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 133 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 69% of its contemporaries.