Machine-learning-assisted universal protein activation in living mice.
Journal:
Cell
Published Date:
May 20, 2025
Abstract
A universal strategy to precisely control protein activation in living animals is crucial for gain-of-function study of proteins under in vivo settings. We herein report CAGE-Prox, a computer-aided proximal decaging strategy for on-demand protein activation as well as protein-protein interaction modulations in living mice. Through machine-learning-assisted evolution of desired aminoacyl-tRNA synthetases (aaRSs), we successfully incorporated chemically caged amino acids into rationally designed "decaging sites" to transiently block target proteins' function, which can be restored in situ via a small-molecule-triggered bioorthogonal cleavage reaction. This method demonstrates broad applicability ranging from activating proteins of interest to cell-type-specific modulation of distinct phenotypes in living systems. Beyond the active-pocket decaging, CAGE-Prox also enables precise control of protein-protein interactions, as exemplified by a "gated" anti-CD3 antibody that permits chemically regulated T cell recruitment and activation at tumor sites. Overall, CAGE-Prox offers a universal platform for time-resolved biological studies and on-demand therapeutic interventions under living conditions.
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