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Furan-based benzene mono- and dicarboxylic acid derivatives as multiple inhibitors of the bacterial Mur ligases (MurC–MurF): experimental and computational characterization

Overview of attention for article published in Perspectives in Drug Discovery and Design, April 2015
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Title
Furan-based benzene mono- and dicarboxylic acid derivatives as multiple inhibitors of the bacterial Mur ligases (MurC–MurF): experimental and computational characterization
Published in
Perspectives in Drug Discovery and Design, April 2015
DOI 10.1007/s10822-015-9843-6
Pubmed ID
Authors

Andrej Perdih, Martina Hrast, Kaja Pureber, Hélène Barreteau, Simona Golič Grdadolnik, Darko Kocjan, Stanislav Gobec, Tom Solmajer, Gerhard Wolber

Abstract

Bacterial resistance to the available antibiotic agents underlines an urgent need for the discovery of novel antibacterial agents. Members of the bacterial Mur ligase family MurC-MurF involved in the intracellular stages of the bacterial peptidoglycan biosynthesis have recently emerged as a collection of attractive targets for novel antibacterial drug design. In this study, we have first extended the knowledge of the class of furan-based benzene-1,3-dicarboxylic acid derivatives by first showing a multiple MurC-MurF ligase inhibition for representatives of the extended series of this class. Steady-state kinetics studies on the MurD enzyme were performed for compound 1, suggesting a competitive inhibition with respect to ATP. To the best of our knowledge, compound 1 represents the first ATP-competitive MurD inhibitor reported to date with concurrent multiple inhibition of all four Mur ligases (MurC-MurF). Subsequent molecular dynamic (MD) simulations coupled with interaction energy calculations were performed for two alternative in silico models of compound 1 in the UMA/D-Glu- and ATP-binding sites of MurD, identifying binding in the ATP-binding site as energetically more favorable in comparison to the UMA/D-Glu-binding site, which was in agreement with steady-state kinetic data. In the final stage, based on the obtained MD data novel furan-based benzene monocarboxylic acid derivatives 8-11, exhibiting multiple Mur ligase (MurC-MurF) inhibition with predominantly superior ligase inhibition over the original series, were discovered and for compound 10 it was shown to possess promising antibacterial activity against S. aureus. These compounds represent novel leads that could by further optimization pave the way to novel antibacterial agents.

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Mendeley readers

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The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 4%
Unknown 47 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 18%
Student > Ph. D. Student 8 16%
Researcher 6 12%
Student > Bachelor 4 8%
Professor 4 8%
Other 2 4%
Unknown 16 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 18%
Chemistry 6 12%
Biochemistry, Genetics and Molecular Biology 5 10%
Pharmacology, Toxicology and Pharmaceutical Science 5 10%
Linguistics 1 2%
Other 4 8%
Unknown 19 39%
Attention Score in Context

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 09 April 2015.
All research outputs
#22,830,981
of 25,457,858 outputs
Outputs from Perspectives in Drug Discovery and Design
#868
of 949 outputs
Outputs of similar age
#241,312
of 280,132 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#3
of 4 outputs
Altmetric has tracked 25,457,858 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 949 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 1st percentile – i.e., 1% 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 280,132 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
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