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Enhanced Hydrogen Bonding by Urea Functionalization Tunes the Stability and Biological Properties of Peptide Amphiphiles.

Huihua XingCaleb WighamSieun Ruth LeeAramis J PereiraLuana J de CamposAgustín S PiccoCristián Huck-IriartCarlos Miguel Santacruz-EscuderoLaura Perez-ChirinosSandun GajaweeraJeffrey R ComerIvan Ramos SasselliSamuel I StuppR Helen ZhaMartin Conda Sheridan
Published in: Biomacromolecules (2024)
Self-assembled nanostructures such as those formed by peptide amphiphiles (PAs) are of great interest in biological and pharmacological applications. Herein, a simple and widely applicable chemical modification, a urea motif, was included in the PA's molecular structure to stabilize the nanostructures by virtue of intermolecular hydrogen bonds. Since the amino acid residue nearest to the lipid tail is the most relevant for stability, we decided to include the urea modification at that position. We prepared four groups of molecules (13 PAs in all), with varying levels of intermolecular cohesion, using amino acids with distinct β-sheet promoting potential and/or containing hydrophobic tails of distinct lengths. Each subset contained one urea-modified PA and nonmodified PAs, all with the same peptide sequence. The varied responses of these PAs to variations in pH, temperature, counterions, and biologically related proteins were examined using microscopic, X-ray, spectrometric techniques, and molecular simulations. We found that the urea group contributes to the stabilization of the morphology and internal arrangement of the assemblies against environmental stimuli for all peptide sequences. In addition, microbiological and biological studies were performed with the cationic PAs. These assays reveal that the addition of urea linkages affects the PA-cell membrane interaction, showing the potential to increase the selectivity toward bacteria. Our data indicate that the urea motif can be used to tune the stability of a wide range of PA nanostructures, allowing flexibility on the biomaterial's design and opening a myriad of options for clinical therapies.
Keyphrases
  • amino acid
  • magnetic resonance imaging
  • machine learning
  • gene expression
  • computed tomography
  • climate change
  • molecular dynamics
  • deep learning
  • high throughput