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Advances in solid-state NMR methods for studying RNA structures and dynamics    

文献类型:期刊文献

中文题名:Advances in solid-state NMR methods for studying RNA structures and dynamics

作者:Jinhan He[1];Xiaole Liu[1];Shenlin Wang[1]

机构:[1]State Key Laboratory of Bioreactor Engineering,East China University of Science and Technology,Shanghai,200237,China

年份:2025

卷号:5

期号:1

起止页码:64

中文期刊名:Magnetic Resonance Letters

外文期刊名:磁共振快报(英文)

基金:supported by the National Natural Science Foundation of China(grant number:22274050);the Shanghai Science and Technology Commission(contract number:23J21900300);the Fundamental Research Funds for the Central Universities.

语种:英文

中文关键词:Solid-state NMR;RNA;Structure;Dynamics;Pulse sequences

摘要:Ribonucleic acid(RNA)structures and dynamics play a crucial role in elucidating RNA functions and facilitating the design of drugs targeting RNA and RNA-protein complexes.However,obtaining RNA structures using conventional biophysical techniques,such as Xray crystallography and solution nuclear magnetic resonance(NMR),presents challenges due to the inherent flexibility and susceptibility to degradation of RNA.In recent years,solid-state NMR(SSNMR)has rapidly emerged as a promising alternative technique for characterizing RNA structure and dynamics.SSNMR has several distinct advantages,including flexibility in sample states,the ability to capture dynamic features of RNA in solid form,and suitability to character RNAs in various sizes.Recent decade witnessed the growth of ^(1)H-detected SSNMR methods on RNA,which targeted elucidating RNA topology and base pair dynamics in solid state.They have been applied to determine the topology of RNA segment in human immunodeficiency virus(HIV)genome and the base pair dynamics of riboswitch RNA.These advancements have expanded the utility of SSNMR techniques within the RNA research field.This review provides a comprehensive discussion of recent progress in ^(1)H-detected SSNMR investigations into RNA structure and dynamics.We focus on the established ^(1)H-detected SSNMR methods,sample preparation protocols,and the implementation of rapid data acquisition approaches.

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