AI 在酶工程领域的创新应用及实践。

蛋白质，作为生命的基石，在生命活动中发挥着关键作用，其结构和功能的研究，对创新药物研发、合成生物学、酶制剂生产等领域，有着极其重要的意义。但传统蛋白质设计面临诸多难题，蛋白质结构复杂，序列空间庞大，依赖专家经验和高通量筛选的设计方式，不仅耗时费力，成功率也难以保证。

如今，AI for Science 已成为全球人工智能发展的新前沿，正在深刻改变着科学研究的范式，并在蛋白质设计领域掀起巨大变革。尤其是在 AlphaFold 等革新性成果面世后，相关研究逐渐走进大众视野，得到了更多关注，同时也进一步促进更多的海内外优秀团队投身于此，从技术、应用等不同环节进行攻坚。

中国科学院深圳先进技术研究院研究员罗小舟教授便是其中的一员，他此前深耕合成生物学，自 2019 年回国后，开始投身 AI 蛋白质研究。在中国上海交通大学近期主办的「未来已来」AI 蛋白质设计峰会上，罗小舟教授对「人工智能驱动的酶工程」主题进行了分享。探讨多模态学习与生成式 AI 在酶设计中的潜在应用，从 UniKP 框架、 ProEnsemble 机器等多个角度阐释了 AI 在酶工程领域的创新应用及实践。

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