Advances that facilitate the study of large RNA structure and dynamics by nuclear magnetic resonance spectroscopy

Abstract

The characterization of functional yet nonprotein coding (nc) RNAs has expanded the role of RNA in the cell from a passive player in the central dogma of molecular biology to an active regulator of gene expression. The misregulation of ncRNA function has been linked with a variety of diseases and disorders ranging from cancers to neurodegeneration. However, a detailed molecular understanding of how ncRNAs function has been limited; due, in part, to the difficulties associated with obtaining high-resolution structures of large RNAs. Tertiary structure determination of RNA as a whole is hampered by various technical challenges, all of which are exacerbated as the size of the RNA increases. Namely, RNAs tend to be highly flexible and dynamic molecules, which are difficult to crystallize. Biomolecular nuclear magnetic resonance (NMR) spectroscopy offers a viable alternative to determining the structure of large RNA molecules that do not readily crystallize, but is itself hindered by some technical limitations. Recently, a series of advancements have allowed the biomolecular NMR field to overcome, at least in part, some of these limitations. These advances include improvements in sample preparation strategies as well as methodological improvements. Together, these innovations pave the way for the study of ever larger RNA molecules that have important biological function.

RNA structures in alternative splicing and back‐splicing

“…Similar to proteins, the 3D structure of RNA can better explain its molecular functions. At present, some experimental methods including nuclear magnetic resonance spectroscopy (NMR; Zhang & Keane, 2019), X‐ray crystallography (Reyes, Garst, & Batey, 2009; Zhang & Ferre‐D'Amare, 2014), and cryo‐electron microscopy (Kappel et al, 2020) have been applied to resolve 3D structures of RNA. Similarly, biological software and tools for 3D structural modeling have also been extensively developed, including SimRNA (Boniecki et al, 2016), ModeRNA (Rother, Rother, Puton, & Bujnicki, 2011), FARNA/FARFAR (Das & Baker, 2007; Das, Karanicolas, & Baker, 2010), VfoldRNA (Zhao, Xu, & Chen, 2017), and so on.…”

NMR Studies of Retroviral Genome Packaging

“…The first reported NMR studies of the intact HIV-1 5′-leader were performed using both chemical ligation of differentially labeled ( 13 C-labeled and un-labeled) fragments and nucleotide specific 2 H editing. Both strategies aimed to enhance spectral sensitivity and resolution and enable detection of NMR chemical shifts and NOE signals for the specific nucleotides of interest [ 409 ]. Although the 1 H- 13 C signals were detectable for the regions of the leader undergoing rapid rotational motions (e.g., the 3′-terminal AUG hairpin), they could not be detected for residues in larger, more globular regions of the RNA undergoing more restricted rotational motions (e.g., the AUG residues when base paired with the upstream U5 element).…”

LinearPartition: linear-time approximation of RNA folding partition function and base-pairing probabilities

“…RNAs are involved in multiple processes, such as catalyzing reactions or guiding RNA modifications ( Bachellerie et al , 2002 ; Doudna and Cech, 2002 ; Eddy, 2001 ), and their functionalities are highly related to structures. However, structure determination techniques, such as X-ray crystallography ( Zhang and Ferré-D’Amaré, 2014 ), nuclear magnetic resonance ( Zhang and Keane, 2019 ) and cryo-electron microscopy ( Lyumkis, 2019 ), though reliable and accurate, are extremely slow and costly. Therefore, fast and accurate computational prediction of RNA structure is useful and desired.…”