Haseltine William A, Hazel Kim, Patarca Roberto
ACCESS Health International, 384 West Lane, Ridgefield, CT 06877, USA.
Feinstein Institutes for Medical Research, 350 Community Dr., Manhasset, NY 11030, USA.
Int J Mol Sci. 2024 Dec 26;26(1):110. doi: 10.3390/ijms26010110.
First believed to be a simple intermediary between the information encoded in deoxyribonucleic acid and that functionally displayed in proteins, ribonucleic acid (RNA) is now known to have many functions through its abundance and intricate, ubiquitous, diverse, and dynamic structure. About 70-90% of the human genome is transcribed into protein-coding and noncoding RNAs as main determinants along with regulatory sequences of cellular to populational biological diversity. From the nucleotide sequence or primary structure, through Watson-Crick pairing self-folding or secondary structure, to compaction via longer distance Watson-Crick and non-Watson-Crick interactions or tertiary structure, and interactions with RNA or other biopolymers or quaternary structure, or with metabolites and biomolecules or quinary structure, RNA structure plays a critical role in RNA's lifecycle from transcription to decay and many cellular processes. In contrast to the success of 3-dimensional protein structure prediction using AlphaFold, RNA tertiary and beyond structures prediction remains challenging. However, approaches involving machine learning and artificial intelligence, sequencing of RNA and its modifications, and structural analyses at the single-cell and intact tissue levels, among others, provide an optimistic outlook for the continued development and refinement of RNA-based applications. Here, we highlight those in gene therapy.
核糖核酸(RNA)最初被认为是脱氧核糖核酸中编码的信息与蛋白质中功能显示的信息之间的简单中介,现在已知它通过其丰富性和复杂、普遍存在、多样且动态的结构具有多种功能。人类基因组约70 - 90%被转录为蛋白质编码和非编码RNA,它们与细胞到群体生物多样性的调控序列一起作为主要决定因素。从核苷酸序列或一级结构,通过沃森 - 克里克配对进行自我折叠或二级结构,到通过更长距离的沃森 - 克里克和非沃森 - 克里克相互作用进行压缩或三级结构,以及与RNA或其他生物聚合物相互作用或四级结构,或与代谢物和生物分子相互作用或五级结构,RNA结构在RNA从转录到衰变的生命周期以及许多细胞过程中起着关键作用。与使用AlphaFold进行三维蛋白质结构预测的成功相比,RNA三级及更高级结构的预测仍然具有挑战性。然而,涉及机器学习和人工智能、RNA及其修饰的测序以及单细胞和完整组织水平的结构分析等方法,为基于RNA的应用的持续发展和完善提供了乐观的前景。在此,我们重点介绍基因治疗中的那些应用。