Abstract
Nature achieves extraordinary mechanical performance by precisely regulating β-structure formation in proteins such as fibroin, elastin, and resilin. Replicating this level of structural control remains a major challenge in protein engineering. Here, we integrate biomimetic design with deep learning–guided de novo protein engineering to create environmentally responsive β-hairpin peptides. Computational optimization enhanced β-hairpin propensity, hydrophilicity, and solvent accessibility while preserving high aqueous solubility. The peptides remain intrinsically disordered in solution but rapidly undergo a β-hairpin transition upon exposure to minimal concentrations of sodium dodecyl sulfate (SDS), a model amphiphilic trigger. This structural conversion drives assembly into mechanically reinforced materials exhibiting increased stiffness and hardness relative to the unfolded state. Our findings provide mechanistic insight into regulated β-structure formation and demonstrate a scalable strategy for programming environmentally triggered protein folding, hierarchical assembly, and mechanical function, opening new opportunities for the rational design of next-generation adaptive biomaterials.
| Original language | English |
|---|---|
| Journal | Communications Materials |
| DOIs | |
| Publication status | Accepted/In press - 20 Jul 2026 |
| MoE publication type | A1 Journal article-refereed |
Funding
This work was supported by the Academy of Finland Grant No. 348628, as well as internal funding from the VTT Technical Research Centre of Finland. The work was also financially supported by the National Science Centre, Poland, Grant No. 2022/45/B/ST4/01184. The solid-state NMR studies were supported by the EU project Fragment-Screen (grant agreement ID: 101094131).
Fingerprint
Dive into the research topics of 'Designed β-hairpin switches for controllable mechanical properties'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver