ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a protein language diffusion model

Understand

Through evolution, nature has presented a set of remarkable protein materials, including elastins, silks, keratins and collagens with superior mechanical performances that play crucial roles in mechanobiology.

• However, going beyond natural designs to discover proteins that meet specified mechanical properties remains challenging.
• Here we report a generative model that predicts protein designs to meet complex nonlinear mechanical property-design objectives.
• Our model leverages deep knowledge on protein sequences from a pre-trained protein language model and maps mechanical unfolding responses to create novel proteins.