深度生成模型设计具有增强转化能力和稳定的mRNA序列
He Zhang1, Hailong Liu2, Yushan Xu3
1Raina Biosciences, Cambridge, MA, USA.
Science (New York, N.Y.)
|August 28, 2025
概括
一个生成性AI模型GEMORNA设计了具有改善表达和稳定性的新型信使RNA (mRNA). 这种先进的RNA技术显示出开发超越疫苗的下一代mRNA疗法的巨大潜力.
科学领域:
- 生物工程
- 人工智能
- 分子生物学
背景情况:
- 传递 RNA (mRNA) 技术已被证明对疫苗有效,但需要针对更广泛的治疗用途进行优化.
- 目前的mRNA设计方法在增强不同应用的表达和稳定性方面存在局限性.
研究的目的:
- 介绍GEMORNA,一种用于设计增强的mRNA分子的新型生成AI模型.
- 评估GEMORNA设计的mRNA用于治疗的性能,包括蛋白质表达和免疫性.
主要方法:
- 使用转换器架构开发mRNA编码序列 (CDS) 和未翻译区域 (UTR).
- 使用火虫光酶试验测试GEMORNA设计的全长mRNA.
- 在体内评估了GEMORNA产生的治疗性mRNA对人体红素 (EPO) 的表达和免疫性.
- 探索GEMORNA在循环RNA设计中的应用,以增强EPO表达和CAR-T细胞抗瘤活性.
主要成果:
- 与基准值相比,GEMORNA设计的mRNA显示火 luciferase的表达增加了41倍.
- 由GEMORNA设计的治疗mRNA可以提高EPO表达的15倍.
- 由GEMORNA生成的mRNA在小鼠中引起了针对COVID疫苗的显著抗体标位.
- 在CAR- T细胞中观察到增强的循环RNA表达和增强的抗瘤细胞毒性.
结论:
- GEMORNA显著增强了mRNA的表达和稳定性,证明了其新疗法开发的潜力.
- 生成型人工智能模型显示了不同RNA格式 (线性和圆形) 和应用的多功能性.
- 深度生成人工智能对超越当前疫苗应用的mRNA疗法有着巨大的前景.
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