Structural and mechanical scaling law behaviour in folded protein hydrogel networks
Year: 2025
Type: article
Abstract: Folded protein hydrogels are generating significant interest for their potential as functional biomaterials with tuneable properties. A detailed understanding of the relationship between their mechanics and structure would reveal their hierarchical design principles and provide rich opportunities for the design of biomaterials for specific medical and healthcare applications. Inspired by theories from soft matter physics, we have investigated the scaling behaviour of the protein volume fraction (ϕ) and its relationship to the underlying structure and mechanics of the protein network through a combination of rheology and small-angle neutron scattering (SANS). Using the globular protein bovine serum albumin (BSA) as a model system and photoactivated chemical crosslinking to retain the colloid-like folded protein structure, we have identified a two-regime behaviour in the storage moduli as a function of ϕ, reminiscent of the strong- and weak- link regimes in a colloidal flocculated model. SANS reveals a heterogeneous protein network structure with fractal-like clusters connected by intercluster regions. Network parameters such as the number of proteins in an average cluster and correlation length scale with ϕ, in line with predictions from the de Gennes blob model. Such distinction between the mechanical and structural scaling relationships provides evidence of a cross-length scale behaviour where intercluster links are important in defining the macroscopic shear response of the system. Insights gained from our integrated structural and mechanical approach will support the future development of novel biomaterials which exploit the folded and functional properties of the protein building block and its responsiveness to mechanical and biochemical cues.
Language: English
Subfield: Molecular Medicine
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $4,470
Awards: G1689194922, G3537589354, G6271517897, G6634603073, IMR-MIP DANSE - Distributed Data Analysis for Neutron Scattering Experiments - CNST, MESONET: Exploiting in situ protein unfolding to understand and control mesoscopic network formation, G8111798673, G8681885083, Exploiting Engineered Polyproteins in the Modular Design of Robust, Tuneable and Biofunctional Hydrogels
OpenAlex ID: W4411137423
