Wei Dongyi, Cheng Peng, Song Ziguo, Liu Yixin, Xu Xiaoran, Huang Xingxu, Wang Xiaolong, Zhang Yu, Shu Wenjie, Wei Yongchang
Department of Radiation and Medical Oncology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China.
Bioinformatics Center of AMMS, Beijing, China.
Mol Syst Biol. 2025 Sep 15. doi: 10.1038/s44320-025-00142-0.
Precise genome editing is crucial for functional studies and therapies. Base editors, while powerful, require optimization for efficiency. Meanwhile, emerging protein design methods and protein language models have driven efficient and intelligent protein engineering. In this study, we employed the Protein Mutational Effect Predictor (ProMEP) to predict the effects of single-site saturated mutations in Cas9 protein, using AncBE4max as the prototype to construct and test 18 candidate point mutations. Based on this, we further predicted combinations of multiple mutations and successfully developed a high-performance variant AncBE4max-AI-8.3, achieving a 2-3-fold increase in average editing efficiency. Introducing the engineered Cas9 into CGBE, YEE-BE4max, ABE-max, and ABE-8e improved their editing performance. The same strategy also substantially improves the efficiencies of HF-BEs. Stable enhancement in editing efficiency was also observed across seven cancer cell lines and human embryonic stem cells. In conclusion, we validated that AI models can serve as more effective protein engineering tools, providing a universal improvement strategy for a series of gene editing tools.
精确的基因组编辑对于功能研究和治疗至关重要。碱基编辑器虽然功能强大，但需要对效率进行优化。与此同时，新兴的蛋白质设计方法和蛋白质语言模型推动了高效且智能的蛋白质工程。在本研究中，我们利用蛋白质突变效应预测器（ProMEP）来预测Cas9蛋白中单位点饱和突变的效应，以AncBE4max为原型构建并测试了18个候选点突变。在此基础上，我们进一步预测了多个突变的组合，并成功开发出高性能变体AncBE4max-AI-8.3，平均编辑效率提高了2至3倍。将工程化的Cas9引入CGBE、YEE-BE4max、ABE-max和ABE-8e中提高了它们的编辑性能。同样的策略也显著提高了HF-BEs的效率。在七种癌细胞系和人类胚胎干细胞中也观察到编辑效率的稳定提高。总之，我们验证了人工智能模型可以作为更有效的蛋白质工程工具，为一系列基因编辑工具提供了通用的改进策略。
