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What if the proteome encodes more biology than we can see from proteins alone? What if protein degradation is not simply cellular disposal, but also a source of biological function? Every cell is continuously breaking down and remodeling proteins, generating a vast and dynamic pool of peptide fragments. We propose that some of these fragments are not inert byproducts, but bioactive molecules with important roles in biology. In our new Essay in @PLOSBiology, “Encrypted immunity mediated by peptides,” Zhenrun J. Zhang, @YMerbl, and I explore this idea through the emerging framework of encrypted immunity: bioactive peptides hidden within larger proteins that can be released through proteolysis and contribute to antimicrobial defense, immune signaling, inflammation, and potentially broader aspects of physiology. AI and machine learning are helping us explore this hidden molecular space at a scale that was previously inaccessible, uncovering candidate peptides in humans, microbes, archaea, venoms, and even extinct organisms. But identifying sequences is only the beginning. The deeper questions are biological: Which peptides are actually produced in vivo? When and where are they generated? How is their release regulated? What functions do they perform? And how do we distinguish meaningful biological signals from the background of protein turnover? Answering these questions will require computation and experimentation to advance together. To me, this points to a broader opportunity for AI in biology: using machines not simply to predict biology, but to help us uncover its hidden organizing principles—and ultimately learn how to engineer them for human health. If this framework holds, it could deepen our understanding of how biological information is encoded and deployed, while opening new directions for therapeutics and diagnostics. Much remains to be learned, and I’m excited about what comes next. Weizmann Institute of Science, @Penn, @CBE_Penn, @PennBioeng, @PennEngineers, @PennMedicine, @PennChemistry, @PennMicro, @PennPsych, @PennSAS. journals.plos.org/plosbiolog…