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Molecular dynamics simulation and linear interaction energy study of d-Glu-based inhibitors of the MurD ligase

Overview of attention for article published in Perspectives in Drug Discovery and Design, August 2013
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Title
Molecular dynamics simulation and linear interaction energy study of d-Glu-based inhibitors of the MurD ligase
Published in
Perspectives in Drug Discovery and Design, August 2013
DOI 10.1007/s10822-013-9673-3
Pubmed ID
Authors

Andrej Perdih, Gerhard Wolber, Tom Solmajer

Abstract

The biosynthetic pathway of the bacterial peptidoglycan, where MurD is an enzyme involved at the intracellular stage of its construction, represents a collection of highly selective macromolecular targets for novel antibacterial drug design. In this study as part of our investigation of the MurD bacterial target two recently discovered classes of the MurD ligase inhibitors were investigated resulting from the lead optimization phases of the N-sulfonamide D-Glu MurD inhibitors. Molecular dynamics simulations, based on novel structural data, in conjunction with the linear interaction energy (LIE) method suggested the transferability of our previously obtained LIE coefficients to further D-Glu based classes of MurD inhibitors. Analysis of the observed dynamical behavior of these compounds in the MurD active site was supported by static drug design techniques. These results complement the current knowledge of the MurD inhibitory mechanism and provide valuable support for the D-Glu paradigm of the inhibitor design.

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The data shown below were collected from the profile of 1 X user 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 4%
Unknown 23 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 21%
Student > Ph. D. Student 5 21%
Student > Bachelor 4 17%
Student > Master 3 13%
Student > Postgraduate 2 8%
Other 2 8%
Unknown 3 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 25%
Biochemistry, Genetics and Molecular Biology 4 17%
Chemistry 3 13%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Linguistics 1 4%
Other 4 17%
Unknown 5 21%
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 31 August 2013.
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
#188,691
of 212,055 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#7
of 7 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 212,055 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.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one.