Literature DB >> 29499459

Computational design of the helical hairpin structure of membrane-active antibacterial peptides based on RSV glycoprotein epitope scaffold.

Jinhua Fu1, Hong Yang2, Jing Wang3.   

Abstract

Peptides with helical hairpin conformation have been found to possess potent membrane activity and can be exploited as the structural scaffold of antibacterial peptides (ABPs). Here, we attempted to computationally design membrane-active ABPs based on the helical hairpin motif of respiratory syncytial virus (RSV) glycoprotein epitope. Dynamics simulations revealed that the epitope peptide Rfe (net charge = -1) cannot effectively interact with and permeabilize bacterial membrane due to the electrostatic repulsion between the negatively charged peptide and anionic membrane surface. The native Rfe can be modified to a cationic peptide Rfe-KKK (net charge = +6) by triple mutation of its positively charged residues Glu256, Asp263 and Asp269 to a basic lysine as well as by C-terminal amidation. As might be expected, the modified peptide was able to target membrane surface with a moderate antibacterial potency (MIC = 50-100 μg/ml). Next, a cyclized version of the linear Rfe-KKK was generated, termed as cycRfe-KKK, which was observed to have improved membrane activity and increased antibacterial potency (MIC < 50 μg/ml) by pre-stabilizing amphipathic hairpin conformation of the peptide.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Antibacterial peptide; Bacterial infection; Glycoprotein epitope; Helical hairpin; Membrane activity; Structural dynamics

Mesh:

Substances:

Year:  2018        PMID: 29499459     DOI: 10.1016/j.compbiolchem.2018.02.013

Source DB:  PubMed          Journal:  Comput Biol Chem        ISSN: 1476-9271            Impact factor:   2.877


  3 in total

1.  Photoinduced reconfiguration to control the protein-binding affinity of azobenzene-cyclized peptides.

Authors:  Kevin Day; John D Schneible; Ashlyn T Young; Vladimir A Pozdin; George Van Den Driessche; Lewis A Gaffney; Raphael Prodromou; Donald O Freytes; Denis Fourches; Michael Daniele; Stefano Menegatti
Journal:  J Mater Chem B       Date:  2020-08-26       Impact factor: 6.331

2.  Affibody-Binding Ligands.

Authors:  Annalisa Barozzi; R Ashton Lavoie; Kevin N Day; Raphael Prodromou; Stefano Menegatti
Journal:  Int J Mol Sci       Date:  2020-05-27       Impact factor: 5.923

3.  Screening of Yeast Display Libraries of Enzymatically Treated Peptides to Discover Macrocyclic Peptide Ligands.

Authors:  John Bowen; John Schneible; Kaitlyn Bacon; Collin Labar; Stefano Menegatti; Balaji M Rao
Journal:  Int J Mol Sci       Date:  2021-02-05       Impact factor: 5.923

  3 in total

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