AI-designed proteins that survive 150 °C and nanonewton forces Proteins are usually fragile machines. Heat them, pull on them, or send them through a high-temperature sterilization step (like those used in hospitals), and most will unfold and aggregate, losing their function. Yet many natural systems—like muscle titin or spider silk—hint that if you organize β-sheet hydrogen bonds in the right way, you can get remarkable mechanical strength and thermal resilience. Bin Zheng and coauthors take that idea and push it to the extreme. Starting from the titin I27 domain, they use an AI+MD pipeline—RFdiffusion for backbone generation, ProteinMPNN for sequence design, ESMFold/AlphaFold2 for structure prediction, and steered/annealing MD for screening—to systematically elongate the force-bearing β strands and maximize backbone hydrogen bonds in a shearing geometry. Across multiple design rounds, they grow the network from 4 to 33 backbone H-bonds, creating a “SuperMyo” series of proteins with unfolding forces above 1,000 pN—roughly 4× stronger than I27 under the same pulling conditions. Remarkably, these proteins not only refold after force, but also retain structure and function after exposure to 150 °C and repeated high-temperature sterilization cycles, and can be used as crosslinkers to make hydrogels that survive those treatments intact. The message is powerful: by combining generative protein design with physics-based simulations, it’s now possible to turn a simple principle—pack as many shear-mode hydrogen bonds as possible into β sheets—into synthetic proteins and materials that rival or surpass nature’s own mechanostable systems, enabling protein-based hydrogels and biomaterials that remain functional under conditions that would normally destroy conventional proteins. Paper: