Literature DB >> 30439615

Membrane targeting cationic antimicrobial peptides.

Daniela Ciumac1, Haoning Gong1, Xuzhi Hu1, Jian Ren Lu2.   

Abstract

Many short cationic peptides are amphiphilic and are often termed antimicrobial peptides (AMPs) as they can kill various microorganisms. These AMPs have largely been discovered from nature, but over the past two decades many biomimetic and de novo designed AMPs have been reported, offering a huge variety of attractive properties for further exploitation. Under the current global endeavour of fighting against antimicrobial resistance, it is useful to introduce AMPs to the biointerface research community and compare their modes of action with conventional antibiotics. Because natural AMPs often have long sequences and other biological functions implicated, they can't be used as antimicrobial agents. However, rational AMP design helps eliminate their shortcomings and more importantly, optimise their structure-function relationship. This review will first introduce the key approaches recently utilised in structural design of AMPs and then introduce the main lipid membrane models such as spread lipid monolayers and vesicles together with the characterisation techniques adopted in early AMP design and development. These studies are crucial towards understanding key factors affecting their efficacy and toxicity. Thus, various interfacial measurements facilitated by different forms of lipid monolayers and bilayers provide valuable support to the selective responses of AMPs to different cell types used in bactericidal assays and cytotoxicity tests, emphasising the link between molecular models and cell models. A number of clinical trials of AMPs have been either under way or completed, demonstrating the huge potential of AMPs in a range of applications.
Copyright © 2018. Published by Elsevier Inc.

Entities:  

Keywords:  Antimicrobial peptides; Antimicrobial resistance; Biocompatibility; Biophysics; Cationic peptides; Lipid membrane; Neutron reflection; Peptide amphiphiles; Peptide surfactants; Toxicity

Mesh:

Substances:

Year:  2018        PMID: 30439615     DOI: 10.1016/j.jcis.2018.10.103

Source DB:  PubMed          Journal:  J Colloid Interface Sci        ISSN: 0021-9797            Impact factor:   8.128


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