Colorado State University researchers used artificial intelligence to modify antibodies so they function as high-signal probes inside living cells, enabling dynamic readouts of gene-expression errors and protein activity. The team trained models to predict sequence and structural changes that maintain binding while enhancing intracellular stability and signal, shortening design cycles for intracellular imaging reagents. The approach couples in silico design with experimental validation to produce antibody-derived probes that reveal subcellular activity in real time, a capability that can accelerate mechanistic studies and drug-target engagement assays in oncology and cell-biology research.