2014/09/24 by Leandro G. Rizzi, L. G. Rizzi, David Head +2
Biochemistry, Genetics and Molecular Biology · Materials Science · Mathematics · Medicine · Physics and Astronomy · #Alzheimer's disease research and treatments #Amyloid fibril #Amyloid β #Anisotropy #Biophysics #Composite material #Condensed matter physics #Elastic modulus #Fibril #Function (biology) #Geometry #Materials science #Mathematics #Nanotechnology #Optics #Peptide #Physics #Protein Structure and Dynamics #Scaling #Self-healing hydrogels #Shear modulus #Statistical physics #Supramolecular Self-Assembly in Materials #Universality (dynamical systems) #cond-mat.soft #physics.bio-ph #q-bio.BM
paper · pdf · doi:10.1103/physrevlett.114.078102
published as Phys. Rev. Lett. 114 (2015) 078102 · Article (6 pages, 4 figures) + Supplementary Information (6 pages, 6 figures)
arxiv created 2014/09/24 · openalex publication_date 2015/02/18 · arxiv updated 2015/03/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Peptide hydrogels have important applications as biomaterials and in nanotechnology, but utilization often depends on their mechanical properties for which we currently have no predictive capability. Here we use a peptide model to simulate the formation of percolating amyloid fibril networks and couple these to the elastic network theory to determine their mechanical properties. We find that the time variation of network length scales can be collapsed onto master curves by using a time scaling function that depends on the peptide interaction anisotropy. The same scaling applies to network mechanics, revealing a nonmonotonic dependence of the shear modulus with time. Our structure-function relationship between the peptide building blocks, network morphology, and network mechanical properties can aid in the design of amyloid fibril networks with tailored mechanical properties.