Core Insights - The article discusses a breakthrough in enzyme technology for plastic degradation, developed by a research team led by Professor Hong Liang from Shanghai Jiao Tong University, utilizing AI to design high-temperature resistant enzymes [1][4]. Group 1: AI and Protein Design - The research team has created an AI model named "Qimingxing" that constructs a functional map of proteins, enabling the efficient design of "super" proteins that are heat, acid, and alkali resistant [1][2]. - The AI model was trained using a dataset of 500 million proteins, tagged with functional labels based on environmental conditions such as temperature, pH, and pressure, making it the largest protein dataset globally [2][3]. Group 2: Efficiency and Automation - The team employs AI to select and modify protein templates to enhance their heat resistance, significantly improving the efficiency of protein design and testing compared to traditional high-throughput screening methods [3]. - An automated laboratory setup is in place to validate AI-designed proteins, creating a feedback loop that continuously optimizes the protein models, referred to as an "automatic driving mode" for proteins [3]. Group 3: Industry Impact - Eight industrial projects have utilized the "Qimingxing" model for protein design, achieving a success rate of 70%, with one biopharmaceutical company reporting a doubling of the lifespan of a designed protein, saving millions annually [3][4]. - The open-source release of the protein model and dataset on GitHub allows global research institutions to access and utilize this technology, potentially leading to a new industrial revolution in synthetic biology [4].