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Development of a novel hybrid antimicrobial peptide for targeted killing of Pseudomonas aeruginosa

Authors
Kim, HyunJang, Ju HyeKim, Sun ChangCho, Ju Hyun
Issue Date
1-Jan-2020
Publisher
ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
Keywords
Antimicrobial peptide; Hybrid peptide; Multidrug-resistant Pseudomonas aeruginosa; OprF; Selective antimicrobial activity
Citation
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY, v.185
Indexed
SCIE
SCOPUS
Journal Title
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
Volume
185
URI
https://scholarworks.bwise.kr/gnu/handle/sw.gnu/7032
DOI
10.1016/j.ejmech.2019.111814
ISSN
0223-5234
Abstract
The emergence of multidrug-resistant (MDR) Pseudomonas aeruginosa, coupled with shrinking antibiotic pipelines, has increased the demand for new antimicrobials with novel mechanisms of action. As the indiscriminate nature of broad-spectrum antimicrobial toxicity may have negative clinical consequences and increase the incidence of resistance, we have developed a P. aeruginosa-selective antimicrobial peptide capable of preferentially killing P. aeruginosa relative to benign microorganisms. A targeting peptide (PA2) that binds specifically to OprF porin on P. aeruginosa was identified by phage display peptide library screening, and a hybrid peptide was constructed by addition of the targeting peptide to GNU7, a potent antimicrobial peptide. The resulting hybrid peptide PA2-GNU7 exhibited potent antimicrobial activity against P. aeruginosa without causing host toxicity. Confocal laser scanning microscopy analysis and time-kill experiments demonstrated that PA2-GNU7 exhibited a high degree of specificity for P. aeruginosa, and rapidly and selectively killed P. aeruginosa cells in mixed cultures. In addition, in vivo treatment efficacy of PA2-GNU7 was significantly greater than that of conventional antibiotics in a mouse model of MDR P. aeruginosa infection. Taken together, the data suggest that PA2-GNU7 may be a promising template for further development as a novel anti-MDR P. aeruginosa therapeutic agent. (C) 2019 Elsevier Masson SAS. All rights reserved.
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