De novo design of high-affinity binders of bioactive helical peptides.

ABSTRACT: Many peptide hormones form an α-helix on binding their receptors^1-4, and sensitive methods for their detection could contribute to better clinical management of disease⁵. De novo protein design can now generate binders with high affinity and specificity to structured proteins^6,7. However, the design of interactions between proteins and short peptides with helical propensity is an unmet challenge. Here we describe parametric generation and deep learning-based methods for designing proteins to address this challenge. We show that by extending RFdiffusion⁸ to enable binder design to flexible targets, and to refining input structure models by successive noising and denoising (partial diffusion), picomolar-affinity binders can be generated to helical

SUBMITTER: Vazquez Torres S 

PROVIDER: S-EPMC10849960 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature