De novo design of protein interactions with learned surface fingerprints.

ABSTRACT: Physical interactions between proteins are essential for most biological processes governing life¹. However, the molecular determinants of such interactions have been challenging to understand, even as genomic, proteomic and structural data increase. This knowledge gap has been a major obstacle for the comprehensive understanding of cellular protein-protein interaction networks and for the de novo design of protein binders that are crucial for synthetic biology and translational applications^2-9. Here we use a geometric deep-learning framework operating on protein surfaces that generates fingerprints to describe geometric and chemical features that are critical to drive protein-protein interactions¹⁰. We hypothesized that these fingerprints capture the key a

SUBMITTER: Gainza P 

PROVIDER: S-EPMC10131520 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature