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Mechanism of Action of Streptogramins and Macrolides

Overview of attention for article published in Drugs, October 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

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7 patents
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1 Wikipedia page

Citations

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104 Dimensions

Readers on

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167 Mendeley
Title
Mechanism of Action of Streptogramins and Macrolides
Published in
Drugs, October 2012
DOI 10.2165/00003495-199600511-00006
Pubmed ID
Authors

Pascal Vannuffel, Carlo Cocito

Abstract

Protein synthesis is catalysed by ribosomes and cytoplasmic factors. Bacterial ribosomes (70S) are made up of 2 subunits (50S and 30S) containing ribosomal RNA (rRNA) and ribosomal proteins: the 30S binds messenger RNA and begins the ribosomal cycle (initiation), whereas 50S binds transfer RNA (tRNA) derivatives and controls elongation. The key reaction, peptide bond formation, is promoted by the catalytic centre of 50S (the peptidyl transferase centre), and the growing peptide chain (peptidyl-tRNA) attached at the donor P site undergoes peptide linkage with an aminoacyl-tRNA at the acceptor A site. This reaction is inhibited by several antibiotics, the best known being chloramphenicol, and the macrolide-lincosamide-streptogramin (MLS) group. These inhibitors have a reversible action, except for streptogramins that are composed of A and B components, which are bacteriostatic alone, but bactericidal when combined. The peptidyl transferase centre has been identified at the 50S surface, and the binding sites of inhibitors have been mapped within this domain: some of these sites overlap (e.g. those of macrolides, and type B streptogramins, which compete for binding to ribosomes). Chloramphenicol blocks the catalytic portion, and A streptogramins the substrate sites of the peptidyl transferase centre. Macrolides and type B streptogramins interfere with the formation of long polypeptides and cause a premature detachment of incomplete peptide chains. The synergism between types A and B streptogramins is due to induction by type A streptogramins of an increased ribosome affinity for type B streptogramins. Microbial resistance to antibiotics mainly involves inactivation of inhibitors and modification of targets (mutations of ribosomal proteins or rRNA genes). Alterations of rRNA bases can induce resistance to a single inhibitor or to a group of antibiotics (e.g. MLSB). The impact of resistance in chemotherapy is less important for streptogramins than for other inhibitors, because the synergistic effect of A and B streptogramins also applies to strains resistant to the MLSB group. It is proposed that mutations and modifications of rRNA bases induce conformational ribosomal changes that prevent antibiotics binding to the target. Conformational changes are also triggered by type A streptogramins: they are responsible for their synergism with type B streptogramins.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 167 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 <1%
Unknown 166 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 34 20%
Student > Ph. D. Student 28 17%
Student > Master 21 13%
Researcher 9 5%
Student > Postgraduate 5 3%
Other 14 8%
Unknown 56 34%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 32 19%
Chemistry 25 15%
Agricultural and Biological Sciences 21 13%
Immunology and Microbiology 7 4%
Medicine and Dentistry 7 4%
Other 16 10%
Unknown 59 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 16 December 2014.
All research outputs
#5,447,195
of 25,374,917 outputs
Outputs from Drugs
#833
of 3,464 outputs
Outputs of similar age
#39,775
of 192,302 outputs
Outputs of similar age from Drugs
#309
of 1,686 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,464 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one has gotten more attention than average, scoring higher than 67% 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 192,302 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 76% of its contemporaries.
We're also able to compare this research output to 1,686 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 67% of its contemporaries.