Structural Insights Into the 5′UG/3′GU Wobble Tandem in Complex With Ba2+ Cation

G•U wobble base pair frequently occurs in RNA structures. The unique chemical, thermodynamic, and structural properties of the G•U pair are widely exploited in RNA biology. In several RNA molecules, the G•U pair plays key roles in folding, ribozyme catalysis, and interactions with proteins. G•U may occur as a single pair or in tandem motifs with different geometries, electrostatics, and thermodynamics, further extending its biological functions. The metal binding affinity, which is essential for RNA folding, catalysis, and other interactions, differs with respect to the tandem motif type due to the different electrostatic potentials of the major grooves. In this work, we present the crystal structure of an RNA 8-mer duplex r[UCGUGCGA]2, providing detailed structural insights into the tandem motif I (5′UG/3′GU) complexed with Ba2+ cation. We compare the electrostatic potential of the presented motif I major groove with previously published structures of tandem motifs I, II (5′GU/3′UG), and III (5′GG/3′UU). A local patch of a strongly negative electrostatic potential in the major groove of the presented structure forms the metal binding site with the contributions of three oxygen atoms from the tandem. These results give us a better understanding of the G•U tandem motif I as a divalent metal binder, a feature essential for RNA functions.

RNAStat: An Integrated Tool for Statistical Analysis of RNA 3D Structures

The 3D architectures of RNAs are essential for understanding their cellular functions. While an accurate scoring function based on the statistics of known RNA structures is a key component for successful RNA structure prediction or evaluation, there are few tools or web servers that can be directly used to make comprehensive statistical analysis for RNA 3D structures. In this work, we developed RNAStat, an integrated tool for making statistics on RNA 3D structures. For given RNA structures, RNAStat automatically calculates RNA structural properties such as size and shape, and shows their distributions. Based on the RNA structure annotation from DSSR, RNAStat provides statistical information of RNA secondary structure motifs including canonical/non-canonical base pairs, stems, and various loops. In particular, the geometry of base-pairing/stacking can be calculated in RNAStat by constructing a local coordinate system for each base. In addition, RNAStat also supplies the distribution of distance between any atoms to the users to help build distance-based RNA statistical potentials. To test the usability of the tool, we established a non-redundant RNA 3D structure dataset, and based on the dataset, we made a comprehensive statistical analysis on RNA structures, which could have the guiding significance for RNA structure modeling. The python code of RNAStat, the dataset used in this work, and corresponding statistical data files are freely available at GitHub (https://github.com/RNA-folding-lab/RNAStat).

Quantitative Structure Activity Relationship (QSAR) study predicts small molecule binding to RNA structure

The diversity of RNA structural elements and their documented role in human diseases make RNA an attractive therapeutic target. However, progress in drug discovery and development has been hindered by challenges in the determination of high-resolution RNA structures and a limited understanding of the parameters that drive RNA recognition by small molecules, including a lack of validated quantitative structure-activity relationships (QSAR). Herein, we developed QSAR models that quantitatively predict both thermodynamic and kinetic-based binding parameters of small molecules and the HIV-1 TAR model RNA system. A set of small molecules bearing diverse scaffolds was screened against the HIV-1-TAR construct using surface plasmon resonance, which provided the binding kinetics and affinities. The data was then analyzed using multiple linear regression (MLR) combined with feature selection to afford robust models for binding of diverse RNA-targeted scaffolds. The predictivity of the model was validated on untested small molecules. The QSAR models presented herein represent the first application of validated and predictive 2D-QSAR using multiple scaffolds against an RNA target. We expect the workflow to be generally applicable to other RNA structures, ultimately providing essential insight into the small molecule descriptors that drive selective binding interactions and, consequently, providing a platform that can exponentially increase the efficiency of ligand design and optimization without the need for high-resolution RNA structures.

Inhibition of SARS-CoV-2 by Targeting Conserved Viral RNA Structures and Sequences

The ongoing COVID-19/Severe Acute Respiratory Syndrome CoV-2 (SARS-CoV-2) pandemic has become a significant threat to public health and has hugely impacted societies globally. Targeting conserved SARS-CoV-2 RNA structures and sequences essential for viral genome translation is a novel approach to inhibit viral infection and progression. This new pharmacological modality compasses two classes of RNA-targeting molecules: 1) synthetic small molecules that recognize secondary or tertiary RNA structures and 2) antisense oligonucleotides (ASOs) that recognize the RNA primary sequence. These molecules can also serve as a “bait” fragment in RNA degrading chimeras to eliminate the viral RNA genome. This new type of chimeric RNA degrader is recently named ribonuclease targeting chimera or RIBOTAC. This review paper summarizes the sequence conservation in SARS-CoV-2 and the current development of RNA-targeting molecules to combat this virus. These RNA-binding molecules will also serve as an emerging class of antiviral drug candidates that might pivot to address future viral outbreaks.

Replication is the key barrier during the dual-host adaption of mosquito-borne flaviviruses

Mosquito-borne flaviviruses (MBFs) adapt to a dual-host transmission circle between mosquitoes and vertebrates. Dual-host affiliated insect-specific flaviviruses (dISFs), discovered from mosquitoes, are phylogenetically similar to MBFs but do not infect vertebrates. Thus, dISF-MBF chimeras could be an ideal model to study the dual-host adaption of MBFs. Using the pseudo-infectious reporter virus particle and reverse genetics systems, we found dISFs entered vertebrate cells as efficiently as the MBFs, but failed to initiate replication. Exchange of the un-translational regions (UTRs) of Donggang virus (DONV), an dISF, with those from Zika virus (ZIKV) rescued DONV replication in vertebrate cells and critical secondary RNA structures were further mapped. Essential UTR-binding host factors were screened for ZIKV replication in vertebrate cells, displaying different binding patterns. Therefore, our data demonstrate a post-entry cross-species transmission mechanism of MBFs, while UTR-host interaction is critical for dual-host adaption.

APOBEC-mediated Editing of SARS-CoV-2 Genomic RNA Impacts Viral Replication and Fitness

During COVID-19 pandemic, mutations of SARS-CoV-2 produce new strains that can be more virulent and evade vaccines. Viral RNA mutations can arise from misincorporation by RNA-polymerases and modification by host factors. Recent SARS-CoV-2 sequence analyses showed a strong bias toward C-to-U mutation, suggesting that host APOBEC cytosine deaminases with immune functions may cause the mutation. We report the experimental evidence demonstrating that APOBEC3A and APOBEC1 can efficiently edit SARS-CoV-2 RNA to produce C-to-U mutation at specific sites. However, APOBEC-editing does not inhibit the viral RNA accumulation in cells. Instead, APOBEC3A-editing of SARS-CoV-2 promotes viral replication/propagation, suggesting that SARS-CoV-2 utilizes the APOBEC-mediated mutations for fitness and evolution. Unlike the unpredictability of random mutations, this study has significant implications in predicting the potential mutations based on the UC/AC motifs and surrounding RNA structures, thus offering a basis for guiding future antiviral therapies and vaccines against the escape mutants.

Cooperativity and Interdependency between RNA Structure and RNA–RNA Interactions

Complex RNA–RNA interactions are increasingly known to play key roles in numerous biological processes from gene expression control to ribonucleoprotein granule formation. By contrast, the nature of these interactions and characteristics of their interfaces, especially those that involve partially or wholly structured RNAs, remain elusive. Herein, we discuss different modalities of RNA–RNA interactions with an emphasis on those that depend on secondary, tertiary, or quaternary structure. We dissect recently structurally elucidated RNA–RNA complexes including RNA triplexes, riboswitches, ribozymes, and reverse transcription complexes. These analyses highlight a reciprocal relationship that intimately links RNA structure formation with RNA–RNA interactions. The interactions not only shape and sculpt RNA structures but also are enabled and modulated by the structures they create. Understanding this two-way relationship between RNA structure and interactions provides mechanistic insights into the expanding repertoire of noncoding RNA functions, and may inform the design of novel therapeutics that target RNA structures or interactions.

MitoVisualize: A resource for analysis of variants in human mitochondrial RNAs and DNA

We present MitoVisualize, a new tool for analysis of the human mitochondrial DNA (mtDNA). MitoVisualize enables visualization of: (1) the position and effect of variants in mitochondrial transfer RNA (tRNA) and ribosomal RNA (rRNA) secondary structures alongside curated variant annotations, (2) data across RNA structures, such as to show all positions with disease-associated variants or with post-transcriptional modifications, and (3) the position of a base, gene or region in the circular mtDNA map, such as to show the location of a large deletion. All visualizations can be easily downloaded as figures for reuse. MitoVisualize can be useful for anyone interested in exploring mtDNA variation, though is designed to facilitate mtDNA variant interpretation in particular. MitoVisualize can be accessed via https://www.mitovisualize.org/. The source code is available at https://github.com/leklab/mito_visualize/.

The different activities of RNA G-quadruplex structures are controlled by flanking sequences

The role of G-quadruplex (G4) RNA structures is multifaceted and controversial. Here, we have used as a model the EBV-encoded EBNA1 and the Kaposi’s sarcoma-associated herpesvirus (KSHV)-encoded LANA1 mRNAs. We have compared the G4s in these two messages in terms of nucleolin binding, nuclear mRNA retention, and mRNA translation inhibition and their effects on immune evasion. The G4s in the EBNA1 message are clustered in one repeat sequence and the G4 ligand PhenDH2 prevents all G4-associated activities. The RNA G4s in the LANA1 message take part in similar multiple mRNA functions but are spread throughout the message. The different G4 activities depend on flanking coding and non-coding sequences and, interestingly, can be separated individually. Together, the results illustrate the multifunctional, dynamic and context-dependent nature of G4 RNAs and highlight the possibility to develop ligands targeting specific RNA G4 functions. The data also suggest a common multifunctional repertoire of viral G4 RNA activities for immune evasion.