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

Many peptide hormones form an α-helix on binding their receptors1-4, 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 proteins6,7. 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 peptide targets by either refining designs generated with other methods, or completely de novo starting from random noise distributions without any subsequent experimental optimization. The RFdiffusion designs enable the enrichment and subsequent detection of parathyroid hormone and glucagon by mass spectrometry, and the construction of bioluminescence-based protein biosensors. The ability to design binders to conformationally variable targets, and to optimize by partial diffusion both natural and designed proteins, should be broadly useful.

Sortase mutants with improved protein thermostability and enzymatic activity obtained by consensus design.

Staphylococcus aureus sortase A (SaSrtA) is an enzyme that anchors proteins to the cell surface of Gram-positive bacteria. During the transpeptidation reaction performed by SaSrtA, proteins containing an N-terminal glycine can be covalently linked to another protein with a C-terminal LPXTG motif (X being any amino acid). Since the sortase reaction can be performed in vitro as well, it has found many applications in biotechnology. Although sortase-mediated ligation has many advantages, SaSrtA is limited by its low enzymatic activity and dependence on Ca2+. In our study, we evaluated the thermodynamic stability of the SaSrtA wild type and found the enzyme to be stable. We applied consensus analysis to further improve the enzyme's stability while at the same time enhancing the enzyme's activity. As a result, we found thermodynamically improved, more active and Ca2+-independent mutants. We envision that these new variants can be applied in conjugation reactions in low Ca2+ environments.