Literature DB >> 9335545

Influence of the angle subtended by the positively charged helix face on the membrane activity of amphipathic, antibacterial peptides.

T Wieprecht1, M Dathe, R M Epand, M Beyermann, E Krause, W L Maloy, D L MacDonald, M Bienert.   

Abstract

To investigate the influence of the angle subtended by the positively charged helix face on membrane activity, six amphipathic alpha-helical peptides with angles between 80 degrees and 180 degrees, but with retained hydrophobicity, hydrophobic moment, and positive overall charge, were designed starting from the sequence of the antibacterial peptide magainin 2. CD investigations revealed that all analogs are in an alpha-helical conformation in vesicle suspension. The ability of the peptides to induce dye release from negatively charged phosphatidylglycerol (PG) vesicles decreased with increasing angle. However, peptides with a large angle of positively charged residues (140-180 degrees) exhibited a considerably higher permeabilizing activity at zwitterionic phosphatidylcholine (PC) and mixed PC/PG (3:1) vesicles than analogs with a small angle (80-120 degrees). In addition, analogs with large angles were more active in antibacterial and hemolytic assays. The antibacterial specificity of these analogs was decreased. Binding investigations showed that peptide binding is favored by a large angle and a high content of negatively charged phospholipid. In contrast, a small angle and a low negative membrane charge enhanced the membrane-permeabilizing efficiency of the bound peptide fraction. All analogs stabilized the bilayer phase of phosphatidylethanolamine over the inverted hexagonal phase. Therefore, a class L mechanism of permeabilization can be excluded. Furthermore, the analogs do not act by the induction of positive curvature strain or by a "carpet-like" mechanism. Our results are in accordance with a pore mechanism: The membrane-permeabilizing efficiency of analogs with enhanced angle of positively charged residues is reduced due to electrostatic repulsion between adjacent helices within the pore, thus resulting in a decreased pore-forming probability and/or pore destabilization.

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Year:  1997        PMID: 9335545     DOI: 10.1021/bi971398n

Source DB:  PubMed          Journal:  Biochemistry        ISSN: 0006-2960            Impact factor:   3.162


  28 in total

1.  Polar angle as a determinant of amphipathic alpha-helix-lipid interactions: a model peptide study.

Authors:  N Uematsu; K Matsuzaki
Journal:  Biophys J       Date:  2000-10       Impact factor: 4.033

2.  Energetics and self-assembly of amphipathic peptide pores in lipid membranes.

Authors:  Assaf Zemel; Deborah R Fattal; Avinoam Ben-Shaul
Journal:  Biophys J       Date:  2003-04       Impact factor: 4.033

3.  Diffusion as a probe of the heterogeneity of antimicrobial peptide-membrane interactions.

Authors:  Kathryn B Smith-Dupont; Lin Guo; Feng Gai
Journal:  Biochemistry       Date:  2010-06-08       Impact factor: 3.162

Review 4.  Antimicrobial peptides: current status and therapeutic potential.

Authors:  Andreas R Koczulla; Robert Bals
Journal:  Drugs       Date:  2003       Impact factor: 9.546

5.  Membrane perturbation induced by interfacially adsorbed peptides.

Authors:  Assaf Zemel; Avinoam Ben-Shaul; Sylvio May
Journal:  Biophys J       Date:  2004-06       Impact factor: 4.033

6.  Secondary structure and lipid contact of a peptide antibiotic in phospholipid bilayers by REDOR.

Authors:  Orsolya Toke; W Lee Maloy; Sung Joon Kim; Jack Blazyk; Jacob Schaefer
Journal:  Biophys J       Date:  2004-07       Impact factor: 4.033

7.  Paradoxical lipid dependence of pores formed by the Escherichia coli alpha-hemolysin in planar phospholipid bilayer membranes.

Authors:  Laura Bakás; Alexandr Chanturiya; Vanesa Herlax; Joshua Zimmerberg
Journal:  Biophys J       Date:  2006-08-25       Impact factor: 4.033

8.  Interaction of 18-residue peptides derived from amphipathic helical segments of globular proteins with model membranes.

Authors:  Chandrasekaran Sivakamasundari; Ramakrishnan Nagaraj
Journal:  J Biosci       Date:  2009-06       Impact factor: 1.826

Review 9.  What can machine learning do for antimicrobial peptides, and what can antimicrobial peptides do for machine learning?

Authors:  Ernest Y Lee; Michelle W Lee; Benjamin M Fulan; Andrew L Ferguson; Gerard C L Wong
Journal:  Interface Focus       Date:  2017-10-20       Impact factor: 3.906

10.  Small changes in the primary structure of transportan 10 alter the thermodynamics and kinetics of its interaction with phospholipid vesicles.

Authors:  Lindsay E Yandek; Antje Pokorny; Paulo F F Almeida
Journal:  Biochemistry       Date:  2008-02-09       Impact factor: 3.162

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