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Efflux pump-mediated antibiotics resistance: Insights from computational structural biology

Overview of attention for article published in Interdisciplinary Sciences: Computational Life Sciences, January 2014
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68 Mendeley
Title
Efflux pump-mediated antibiotics resistance: Insights from computational structural biology
Published in
Interdisciplinary Sciences: Computational Life Sciences, January 2014
DOI 10.1007/s12539-014-0191-3
Pubmed ID
Authors

Nadine Fischer, Martin Raunest, Thomas H. Schmidt, Dennis C. Koch, Christian Kandt

Abstract

The continuous rise of bacterial resistance against formerly effective pharmaceuticals is a major challenge for biomedical research. Since the first computational studies published seven years ago the simulation-based investigation of antibiotics resistance mediated by multidrug efflux pumps of the resistance nodulation division (RND) protein super family has grown into a vivid field of research. Here we review the employment of molecular dynamics computer simulations to investigate RND efflux pumps focusing on our group's recent contributions to this field studying questions of energy conversion and substrate transport in the inner membrane antiporter AcrB in Escherichia coli as well as access regulation and gating mechanism in the outer membrane efflux ducts TolC and OprM in E. coli and Pseudomonas aeruginosa.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 1%
United States 1 1%
Serbia 1 1%
Italy 1 1%
Unknown 64 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 26%
Student > Ph. D. Student 15 22%
Student > Master 8 12%
Student > Bachelor 7 10%
Student > Doctoral Student 4 6%
Other 8 12%
Unknown 8 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 29%
Biochemistry, Genetics and Molecular Biology 11 16%
Pharmacology, Toxicology and Pharmaceutical Science 8 12%
Physics and Astronomy 6 9%
Immunology and Microbiology 2 3%
Other 10 15%
Unknown 11 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 31 January 2014.
All research outputs
#15,409,624
of 25,736,439 outputs
Outputs from Interdisciplinary Sciences: Computational Life Sciences
#82
of 302 outputs
Outputs of similar age
#178,954
of 324,822 outputs
Outputs of similar age from Interdisciplinary Sciences: Computational Life Sciences
#3
of 9 outputs
Altmetric has tracked 25,736,439 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 302 research outputs from this source. They receive a mean Attention Score of 2.3. This one has gotten more attention than average, scoring higher than 71% 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 324,822 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.