Interactions of a class IIb bacteriocin with a model lipid bilayer, investigated through molecular dynamics simulations

Panagiota K. Kyriakou, Bie Ekblad, Per Eugen Kristiansen, Yiannis Kaznessis

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

The emergence of antibiotic resistant microorganisms poses an alarming threat to global health. Antimicrobial peptides (AMPs) are considered a possible effective alternative to conventional antibiotic therapies. An understanding of the mechanism of action of AMPs is needed in order to better control and optimize their bactericidal activity. Plantaricin EF is a heterodimeric AMP, consisting of two peptides Plantaricin E (PlnE) and Plantaricin F (PlnF). We studied the behavior of these peptides on the surface of a model lipid bilayer. We identified the residues that facilitate peptide-peptide interactions. We also identified residues that mediate interactions of the dimer with the membrane. PlnE interacts with the membrane through amino acids at both its termini, while only the N terminus of PlnF approaches the membrane. By comparing the activity of single-site mutants of the two-peptide bacteriocin and the simulations of the bacteriocin on the surface of a model lipid bilayer, structure activity relationships are proposed. These studies allow us to generate hypotheses that relate biophysical interactions observed in simulations with the experimentally measured activity. We find that single-site amino acid substitutions result in markedly stronger antimicrobial activity when they strengthen the interactions between the two peptides, while, concomitantly, they weaken peptide-membrane association. This effect is more pronounced in the case of the PlnE mutant (G20A), which interacts the strongest with PlnF and the weakest with the membrane while displaying the highest activity.

Original languageEnglish (US)
Pages (from-to)824-835
Number of pages12
JournalBiochimica et Biophysica Acta - Biomembranes
Volume1858
Issue number4
DOIs
StatePublished - Apr 1 2016

Bibliographical note

Funding Information:
This work utilized the high-performance computational resources of the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI- 1053575. Computational support from the Minnesota Supercomputing Institute (MSI) is gratefully acknowledged. This projectwas funded partially by the Norwegian Centennial Chair program, a cooperation in research and academic education between the Norwegian University of Life Science, the University of Oslo and the University of Minnesota. This project was also funded by grants from the National Institutes of Health (GM111358) and from the National Science Foundation (CBET- 1412283).

Funding Information:
This work utilized the high-performance computational resources of the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1053575 . Computational support from the Minnesota Supercomputing Institute (MSI) is gratefully acknowledged. This project was funded partially by the Norwegian Centennial Chair program , a cooperation in research and academic education between the Norwegian University of Life Science, the University of Oslo and the University of Minnesota. This project was also funded by grants from the National Institutes of Health ( GM111358 ) and from the National Science Foundation ( CBET-1412283 ).

Publisher Copyright:
© 2016 Elsevier B.V. All rights reserved.

Keywords

  • Antibiotic resistance
  • Antimicrobial peptides
  • Bacteriocins

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