Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Department of Bioengineering, Stanford University, Stanford, CA, USA.
Nat Rev Genet. 2023 Jun;24(6):401-414. doi: 10.1038/s41576-022-00567-5. Epub 2023 Jan 12.
RNAs are central to fundamental biological processes in all known organisms. The set of possible intramolecular interactions of RNA nucleotides defines the range of alternative structural conformations of a specific RNA that can coexist, and these structures enable functional catalytic properties of RNAs and/or their productive intermolecular interactions with other RNAs or proteins. However, the immense combinatorial space of potential RNA sequences has precluded predictive mapping between RNA sequence and molecular structure and function. Recent advances in high-throughput approaches in vitro have enabled quantitative thermodynamic and kinetic measurements of RNA-RNA and RNA-protein interactions, across hundreds of thousands of sequence variations. In this Review, we explore these techniques, how they can be used to understand RNA function and how they might form the foundations of an accurate model to predict the structure and function of an RNA directly from its nucleotide sequence. The experimental techniques and modelling frameworks discussed here are also highly relevant for the sampling of sequence-structure-function space of DNAs and proteins.
RNAs 在所有已知生物的基本生物过程中都起着核心作用。RNA 核苷酸的可能分子内相互作用集合定义了特定 RNA 可以共存的一系列替代结构构象，这些结构使 RNA 的催化功能和/或其与其他 RNA 或蛋白质的有效分子间相互作用成为可能。然而，潜在 RNA 序列的巨大组合空间使得 RNA 序列与其分子结构和功能之间的预测映射变得不可能。最近在体外高通量方法方面的进展使得能够对成千上万种序列变化的 RNA-RNA 和 RNA-蛋白质相互作用进行定量热力学和动力学测量。在这篇综述中，我们探讨了这些技术，以及它们如何用于理解 RNA 的功能，以及它们如何成为直接从核苷酸序列预测 RNA 结构和功能的准确模型的基础。这里讨论的实验技术和建模框架对于 DNA 和蛋白质的序列-结构-功能空间的采样也具有高度相关性。
