Post-crystallization Improvement of RNA Crystal Diffraction Quality

The Unpaved Road of Non-Coding RNA Structure-Function Relationships: Current Knowledge, Available Methodologies, and Future Trends

The genomes from complex eukaryotes are enriched in non-coding genes whose transcription products (non-coding RNAs) are involved in the regulation of genomic output at different levels. Non-coding RNA action is predominantly driven by sequence and structural motifs that interact with specific functional partners. Despite the exponential growth in primary RNA sequence data facilitated by next-generation sequencing studies, the availability of tridimensional RNA data is comparatively more limited. The subjacent reasons for this relative lack of information regarding RNA structure are related to the specific chemical nature of RNA molecules and the limitations of the currently available methods for structural characterization of biomolecules. In this review, we describe and analyze the different structural motifs involved in non-coding RNA function and the wet-lab and computational methods used to characterize their structure-function relationships, highlighting the current need for detailed structural studies to explore the molecular determinants of non-coding RNA function.

tRNA Fusion to Streamline RNA Structure Determination: Case Studies in Probing Aminoacyl-tRNA Sensing Mechanisms by the T-Box Riboswitch

RNAs are prone to misfolding and are often more challenging to crystallize and phase than proteins. Here, we demonstrate that tRNA fusion can streamline the crystallization and structure determination of target RNA molecules. This strategy was applied to the T-box riboswitch system to capture a dynamic interaction between the tRNA 3′-UCCA tail and the T-box antiterminator, which senses aminoacylation. We fused the T-box antiterminator domain to the tRNA anticodon arm to capture the intended interaction through crystal packing. This approach drastically improved the probability of crystallization and successful phasing. Multiple structure snapshots captured the antiterminator loop in an open conformation with some resemblance to that observed in the recent co-crystal structures of the full-length T box riboswitch–tRNA complex, which contrasts the resting, closed conformation antiterminator observed in an earlier NMR study. The anticipated tRNA acceptor–antiterminator interaction was captured in a low-resolution crystal structure. These structures combined with our previous success using prohead RNA–tRNA fusions demonstrates tRNA fusion is a powerful method in RNA structure determination.

Computational modeling of RNA 3D structure based on experimental data

RNA molecules are master regulators of cells. They are involved in a variety of molecular processes: they transmit genetic information, sense cellular signals and communicate responses, and even catalyze chemical reactions. As in the case of proteins, RNA function is dictated by its structure and by its ability to adopt different conformations, which in turn is encoded in the sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore the majority of known RNAs remain structurally uncharacterized. To address this problem, predictive computational methods were developed based on the accumulated knowledge of RNA structures determined so far, the physical basis of the RNA folding, and taking into account evolutionary considerations, such as conservation of functionally important motifs. However, all theoretical methods suffer from various limitations, and they are generally unable to accurately predict structures for RNA sequences longer than 100-nt residues unless aided by additional experimental data. In this article, we review experimental methods that can generate data usable by computational methods, as well as computational approaches for RNA structure prediction that can utilize data from experimental analyses. We outline methods and data types that can be potentially useful for RNA 3D structure modeling but are not commonly used by the existing software, suggesting directions for future development.