通过语言模型启用平台发现多样化和高质量的mRNA封闭酶
Tianze Wang1, Bowen R Qin1, Sihong Li1
1Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.
Science advances
|April 9, 2025
概括
SYMPLEX是一个使用大型语言模型的新平台,有效地挖掘生物技术的遗传部分. 它确定了新的mRNA封闭酶,其中一些显示出用于疫苗开发的卓越活性.
科学领域:
- 合成生物学 合成生物学
- 生物工程是生物工程.
- 生物技术是生物技术.
背景情况:
- 高质量的遗传部件对于下一代生物技术至关重要,但目前的基因挖掘方法有限.
- 现有的方法依赖于序列同样性或专家知识,阻碍了全面的遗传部分目录开发.
研究的目的:
- 开发SYMPLEX,一个通用的基因挖掘平台,利用大型语言模型来提取知识.
- 应用SYMPLEX用于参与信使RNA (mRNA) 封闭的采矿酶.
主要方法:
- 简单利用大型语言模型从生物医学文献和数据库提取知识.
- 该平台用于识别负责真核mRNA封闭的酶.
- 对已识别的酶候选物进行了实验验证.
主要成果:
- 简单的成功地挖掘了数千种不同的mRNA封闭酶候选人,有可追溯的证据.
- 在46个被测试的候选物种中,有14个在体内表现出跨物种限制活动.
- 与商业疫苗封闭酶相比,两种候选药物在体外表现出更高的活性.
结论:
- SYMPLEX为功能性基因挖掘提供了一个新的范式,克服了传统方法的局限性.
- 该平台加速知识发现,并为合成生物学基础研究提供工具.
- 已识别的封闭酶在mRNA疫苗生产和生物技术中具有潜在的应用.
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