A denoising diffusion model from David Baker's Institute for Protein Design generates macrocyclic peptide binders against arbitrary protein targets. Tested on four targets, it produced nanomolar-affinity binders from fewer than 20 designs each, with crystal structures matching the computational models to within ~1.5 Å. Published in Nature Chemical Biology, the work signals that AI can now yield drug-like cyclic peptides on demand.
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