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

ABSTRACT: 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 pretrained protein language model and maps mechanical unfolding responses to create proteins. Via full-atom molecular simulations for direct validation, we demonstrate that the designed proteins are de novo, and fulfill the targeted mechanical properties, including unfolding

SUBMITTER: Ni B 

PROVIDER: S-EPMC10849601 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature