De novo design of protein binders to bioactive peptides: from hormones to snake toxins

Abstract

Recent advancements in deep learning methods for protein design and structure prediction have demonstrated the potential of de novo proteins to replace antibodies as affinity reagents, offering cost-effective production, increased stability, and robust platforms for therapeutics and diagnostics. In this work, we set out to design de novo protein binders for two classes of bioactive peptides: hormones which adopt α-helical structures, and lethal snake toxins from the three-finger toxin (3FTX) family. Using deep learning-based methods, we generated high-affinity binders for both targets. These binders enable hormone detection via mass spectrometry and the creation of bioluminescence-based biosensors. Additionally, our designed proteins effectively neutralize 3FTXs in vitro and protect mice from lethal neurotoxin challenges. While further development is necessary to translate these designs into practical diagnostics and therapeutics, this work demonstrates their potential as robust reagents for hormone detection and as safer, widely accessible antivenoms.