使用受限制博尔兹曼机器设计分子RNA开关
Jorge Fernandez-de-Cossio-Diaz1,2, Pierre Hardouin3, Francois-Xavier Lyonnet du Moutier3
1CNRS UMR 8023, Laboratory of Physics of the Ecole Normale Supérieure & PSL Research, Sorbonne Université, Paris, France.
Nature communications
|December 18, 2025
概括
研究人员使用机器学习设计了新型的核糖切换器 (riboswitch aptamers). 这些设计的RNA分子可以在对代谢物的反应中切换结构,类似于自然的核糖转换器.
科学领域:
- RNA生物学的RNA生物学
- 计算生物学是一种计算生物学.
- 生物化学 生化学
背景情况:
- 利博开关是全性RNA分子,通过改变对代谢物结合的构造来调节基因表达.
- 亚胺是负责代谢物识别和构造变化的 рибо开关的核心成分.
- 功能性RNA分子的新设计仍然是合成生物学中的一个重大挑战.
研究的目的:
- 开发一种机器学习方法,用于新设计类似于 рибо交换机的体.
- 为了产生具有所需全osteric 功能的新型 SAM-I рибо交换机体.
- 为了实验验证设计的aptamers的形状切换能力.
主要方法:
- 利用受限制的博尔兹曼机器 (RBM) 来从同源RNA序列中学习生成模型.
- 应用RBM来设计新的SAM-I рибо开关阿普坦.
- 采用化学探测技术 (SHAPE和DMS) 进行高通量实验验证.
- 开发了一种定制的分析管道,用于评估设计序列中的构造变化.
主要成果:
- RBM模型准确地捕获了四个家族的自然体的序列保护,共变和多样性.
- 476个新设计的SAM-I体被实验性地与201个自然序列一起探测.
- 具有高RBM得分和20-40%的序列分歧的设计aptamer在SAM诱导的构造转换中显示了~30%的成功率.
- 设计的体体能够切换形状的能力与特定的能量特征相关.
结论:
- 受限制的博尔茨曼机器对于功能性 рибо交换机的 de novo 设计是有效的.
- 设计的体可以模仿自然体开关的体调节机制.
- 该研究提供了对RNA结构转换的能量决定因素的见解,为设计基于RNA的新型调节元件铺平了道路.
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