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https://doi.org/10.1007/82_201...
Part of book or chapter of book . 2015 . Peer-reviewed
License: Springer TDM
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Anti-virulence Strategies to Target Bacterial Infections

Authors: Mühlen, Sabrina; Dersch, Petra;

Anti-virulence Strategies to Target Bacterial Infections

Abstract

Resistance of important bacterial pathogens to common antimicrobial therapies and the emergence of multidrug-resistant bacteria are increasing at an alarming rate and constitute one of our greatest challenges in the combat of bacterial infection and accompanied diseases. The current shortage of effective drugs, lack of successful prevention measures and only a few new antibiotics in the clinical pipeline demand the development of novel treatment options and alternative antimicrobial therapies. Our increasing understanding of bacterial virulence strategies and the induced molecular pathways of the infectious disease provides novel opportunities to target and interfere with crucial pathogenicity factors or virulence-associated traits of the bacteria while bypassing the evolutionary pressure on the bacterium to develop resistance. In the past decade, numerous new bacterial targets for anti-virulence therapies have been identified, and structure-based tailoring of intervention strategies and screening assays for small-molecule inhibitors of such pathways were successfully established. In this chapter, we will take a closer look at the bacterial virulence-related factors and processes that present promising targets for anti-virulence therapies, recently discovered inhibitory substances and their promises and discuss the challenges, and problems that have to be faced.

Country
Germany
Keywords

Bacteria, Bacterial Proteins, Virulence, Virulence Factors, Animals, Humans, Bacterial Infections, Anti-Bacterial Agents

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    143
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
143
Top 1%
Top 10%
Top 10%