The tool we used to design these binders is Prometheus, a protein design method that uses an inverse folding model as a reinforcement learning agent to achieve self-optimization. In our workflow, the model achieves automatic updates of parameters through "generation-evaluation-optimization" loop, gradually learning the ability to generate better binders, which greatly reduces the scale and cost of screening and experimental verification, and significantly enhances experimental success rates.