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De novo design of selective antibiotic peptides by incorporation of unnatural amino acids

  • Rickey P. Hicks(corresponding author)
    ,
  • Jayendra B. Bhonsle
    ,
  • Divakaramenon Venugopal
    ,
  • Brandon W. Koser
    ,
  • Alan J. Magill
*Corresponding author for this work
  • East Carolina University
    ,
  • Walter Reed Army Institute of Research
Scholary Output:
Contribution to journal
Article
Peer-review

Abstract

The evolution of drug-resistant bacteria is one of the most critical problems facing modern medicine and requires the development of new drugs that exhibit their antibacterial activity via novel mechanisms of action. One potential source of new drugs could be the naturally occurring peptides that exhibit antimicrobial activity via membrane disruption. To develop antimicrobial peptides exhibiting increased potency and selectivity against Gram positive, Gram negative, and Mycobacterium bacteria coupled with reduced hemolytic activity, peptides containing unnatural amino acids have been designed, synthesized, and evaluated. These compounds were designed on the basis of the electrostatic surface potential maps derived from the NMR determined SDS and DPC micelle-bound conformations of (Ala8,13,18)magainin-2 amide. Unnatural amino acids were incorporated into the polypeptide backbone to control the structural and physicochemical properties of the peptides to introduce organism selectivity and potency. The methods and results of this investigation are described below.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 3026-3036 (11 pages)

Journal (Volume, Issue Number)

Journal of Medicinal Chemistry (Volume 50, Issue 13)

Publication milestones

  • Published - 06/28/2007

Publication status

Published - 06/28/2007

ISSN

0022-2623

Publication IDs

  • Scopus: 34347229452
  • PubMed: 17547385

Publication metrics

Metrics

Scopus
citations
SciVal
citations
50
SciVal
FWCI
1.48
SciVal
Author count
5
SciVal
Paper percentile
88
Fractional count
1
Fractional count
0.20
Fractional count
4
Fractional count
0.80
Fractional count
1
Fractional count
1

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Captures
55
Citation count
62