Genome-wide mapping of SARS-CoV-2 RNA structures identifies therapeutically-relevant elements

Characterization of the binding features between SARS-CoV-2 5'-proximal transcripts of genomic RNA and nucleocapsid proteins

Packaging signals (PSs) of coronaviruses (CoVs) are specific RNA elements recognized by nucleocapsid (N) proteins that direct the selective packaging of genomic RNAs (gRNAs). These signals have been identified in the coding regions of the nonstructural protein 15 (Nsp 15) in CoVs classified under Embecovirus, a subgenus of betacoronaviruses (beta-CoVs). The PSs in other alpha- and beta-CoVs have been proposed to reside in the 5'-proximal regions of gRNAs, supported by comprehensive phylogenetic evidence. However, experimental data remain limited. In this study, we investigated the interactions between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) 5'-proximal gRNA transcripts and N proteins using electrophoretic mobility shift assays (EMSAs). Our findings revealed that the in vitro synthesized 5'-proximal gRNA transcripts of CoVs can shift from a major conformation to alternative conformations. We also observed that the conformer comprising multiple stem-loops (SLs) is preferentially bound by N proteins. Deletions of the 5'-proximal structural elements of CoV gRNA transcripts, SL1 and SL5a/b/c in particular, were found to promote the formation of alternative conformations. Furthermore, we identified RNA-binding peptides from a pool derived from SARS-CoV N protein. These RNA-interacting peptides were shown to preferentially bind to wild-type SL5a RNA. In addition, our observations of N protein condensate formation in vitro demonstrated that liquid-liquid phase separation (LLPS) of N proteins with CoV-5'-UTR transcripts was influenced by the presence of SL5a/b/c. In conclusion, these results collectively reveal previously uncharacterized binding features between the 5'-proximal transcripts of CoV gRNAs and N proteins.

DRLiPS: a novel method for prediction of druggable RNA-small molecule binding pockets using machine learning

Ribonucleic Acid (RNA) is the central conduit for information transfer in the cell. Identifying potential RNA targets in disease conditions is a challenging task, given the vast repertoire of functional non-coding RNAs in a human cell. A potential druggable target must satisfy several criteria, including disease association, cellular accessibility, binding pockets for drug-like molecules, and minimal cross-reactivity. While several methods exist for prediction of druggable proteins, they cannot be repurposed for RNAs due to fundamental differences in their binding modality. Taking all these constraints into account, a new structure-based model, Druggable RNA-Ligand binding Pocket Selector (DRLiPS), is developed here to predict binding site-level druggability of any given RNA target. A novel strategy for sampling negative binding sites in RNA structures using three parallel approaches is demonstrated here to improve model specificity: backbone motif search, exhaustive pocket prediction, and blind docking. An external blind test dataset has also been curated to showcase the model's generalizability to both experimental and modelled apo state RNA structures. DRLiPS has achieved an F1-score of 0.70, precision of 0.61, specificity of 0.89, and recall of 0.73 on this external test dataset, outperforming two existing methods, DrugPred_RNA and RNACavityMiner. Further analysis indicates that the features selected for model-building generalize well to both apo and holo states with a backbone RMSD tolerance of 3 Å. It can also predict the effect of binding site single point mutations on druggability, which can aid in optimizing synthetic RNA aptamers for small molecule recognition. The DRLiPS model is freely accessible at https://web.iitm.ac.in/bioinfo2/DRLiPS/.

The coronavirus helicase synergizes with the viral polymerase to enable rapid RNA synthesis through duplex RNA

The genome of most positive-sense (+)RNA viruses encodes a helicase, such as the coronavirus (CoV) nsp13-helicase, but little is known about their actual function, despite being absolutely essential for CoV replication. The CoV polymerase associates with two nsp13-helicases, which translocates in the opposite direction, raising questions about nsp13-helicase role during viral RNA synthesis. Using magnetic tweezers, we show that nsp13-helicase specifically associates with the CoV polymerase and tranlocates on the strand opposite to the template, increasing the overall RNA synthesis rate on a double-stranded (ds) RNA template by ten-fold. Nsp13-helicase utilizes both ATP hydrolysis and allostery to assist the CoV polymerase through the dsRNA fork. Our kinetic modelling provides the energy landscape of the two nsp13-helicases association with the polymerase and describes the nucleotide addition mechanochemistry of the resulting complex. Our study demonstrates a new function for (+)RNA virus helicase and deepens the understanding of CoV replication and transcription.

Secondary structure of the SARS-CoV-2 genome is predictive of nucleotide substitution frequency

Accurate estimation of the effects of mutations on SARS-CoV-2 viral fitness can inform public-health responses such as vaccine development and predicting the impact of a new variant; it can also illuminate biological mechanisms including those underlying the emergence of variants of concern. Recently, Lan et al. reported a model of SARS-CoV-2 secondary structure and its underlying dimethyl sulfate reactivity data (Lan et al., 2022). I investigated whether base reactivities and secondary structure models derived from them can explain some variability in the frequency of observing different nucleotide substitutions across millions of patient sequences in the SARS-CoV-2 phylogenetic tree. Nucleotide basepairing was compared to the estimated 'mutational fitness' of substitutions, a measurement of the difference between a substitution's observed and expected frequency that is correlated with other estimates of viral fitness (Bloom and Neher, 2023). This comparison revealed that secondary structure is often predictive of substitution frequency, with significant decreases in substitution frequencies at basepaired positions. Focusing on the mutational fitness of C→U, the most common type of substitution, I describe C→U substitutions at basepaired positions that characterize major SARS-CoV-2 variants; such mutations may have a greater impact on fitness than appreciated when considering substitution frequency alone.

A Cascade of Conformational Switches in SARS-CoV-2 Frameshifting: Coregulation by Upstream and Downstream Elements

Targeting ribosomal frameshifting has emerged as a potential therapeutic intervention strategy against COVID-19. In this process, a -1 shift in the ribosomal reading frame encodes alternative viral proteins. Any interference with this process profoundly affects viral replication and propagation. For SARS-CoV-2, two RNA sites associated with ribosomal frameshifting are positioned on the 5' and 3' of the frameshifting residues. Although much attention has been focused on the 3' frameshift element (FSE), the 5' stem-loop (attenuator hairpin, AH) can play a role. Yet the relationship between the two regions is unknown. In addition, multiple folds of the FSE and FSE-containing RNA regions have been discovered. To gain more insight into these RNA folds in the larger sequence context that includes AH, we apply our graph-theory-based modeling tools to represent RNA secondary structures, "RAG" (RNA-As-Graphs), to generate conformational landscapes that suggest length-dependent conformational distributions. We show that the AH region can coexist as a stem-loop with main and alternative 3-stem pseudoknots of the FSE (dual graphs 3_6 and 3_3 in our notation) but that an alternative stem 1 (AS1) can disrupt the FSE pseudoknots and trigger other folds. A critical length for AS1 of 10-bp regulates key folding transitions. Together with designed mutants and available experimental data, we present a sequential view of length-dependent folds during frameshifting and suggest their mechanistic roles. These structural and mutational insights into both ends of the FSE advance our understanding of the SARS-CoV-2 frameshifting mechanism by suggesting how alternative folds play a role in frameshifting and defining potential therapeutic intervention techniques that target specific folds.

Targeted Covalent Modification Strategies for Drugging the Undruggable Targets

The term "undruggable" refers to proteins or other biological targets that have been historically challenging to target with conventional drugs or therapeutic strategies because of their structural, functional, or dynamic properties. Drugging such undruggable targets is essential to develop new therapies for diseases where current treatment options are limited or nonexistent. Thus, investigating methods to achieve such drugging is an important challenge in medicinal chemistry. Among the numerous methodologies for drug discovery, covalent modification of therapeutic targets has emerged as a transformative strategy. The covalent attachment of diverse functional molecules to targets provides a powerful platform for creating highly potent drugs and chemical tools as well the ability to provide valuable information on the structures and dynamics of undruggable targets. In this review, we summarize recent examples of chemical methods for the covalent modification of proteins and other biomolecules for the development of new therapeutics and to overcome drug discovery challenges and highlight how such methods contribute toward the drugging of undruggable targets. In particular, we focus on the use of covalent chemistry methods for the development of covalent drugs, target identification, drug screening, artificial modulation of post-translational modifications, cancer specific chemotherapies, and nucleic acid-based therapeutics.

SARS-CoV-2 CoCoPUTs: analyzing GISAID and NCBI data to obtain codon statistics, mutations, and free energy over a multiyear period

A consistent area of interest since the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been the sequence composition of the virus and how it has changed over time. Many resources have been developed for the storage and analysis of SARS-CoV-2 data, such as GISAID (Global Initiative on Sharing All Influenza Data), NCBI, Nextstrain, and outbreak.info. However, relatively little has been done to compile codon usage data, codon-level mutation data, and secondary structure data into a single database. Here, we assemble the aforementioned data and many additional virus attributes in a new database entitled SARS-CoV-2 CoCoPUTs. We begin with an overview of the composition and overlap between two of the largest sources of SARS-CoV-2 sequence data: GISAID and NCBI Virus (GenBank). We then evaluate different types of sequence curation strategies to reduce the dataset of millions of sequences to only one sequence per Pango lineage variant. We then performed specific analyses on the coding sequences (CDSs), including calculating codon usage, codon pair usage, dinucleotides, junction dinucleotides, mutations, GC content, effective number of codons (ENCs), and effective number of codon pairs (ENCPs). We have also performed whole-genome secondary RNA structure prediction calculations for each variant, using the LinearPartition software and modified selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) data that are available online. Finally, we compiled all the data into our resource, SARS-CoV-2 CoCoPUTs, and paired many of the resulting statistics with variant proportion data over time in order to derive trends in viral evolution. Although the overall codon usage of SARS-CoV-2 did not change drastically, in line with the previous literature on this subject, we did observe that while overall GC% content decreased, GC% of the third position in the codon was more positive relative to overall GC% content between February 2021 and July 2023. Over the same interval, we noted that both synonymous and nonsynonymous mutations increased in number, with nonsynonymous mutations outpacing synonymous mutations at a rate of 3:1. We noted that the predicted whole-genome secondary structures nearly all contained the previously described virus-activated inhibitor of translation (VAIT) stem loops, validating for the first time their existence in a whole-genome secondary structure prediction for many SARS-CoV-2 variants (as opposed to previous local secondary structure predictions). We also separately produced a synonymous mutation-deprived set of SARS-CoV-2 variant sequences and repeated the secondary structure calculations on this set. This revealed an interesting trend of reduced ensemble free energy compared to the unaltered variant structures, indicating that synonymous mutations play a role in increasing the free energy of viral RNA molecules. These data both validate previous studies describing increases in viral free energy in human viruses over time and indicate a possible role for synonymous mutations in viral biology.

Chemical-guided SHAPE sequencing (cgSHAPE-seq) informs the binding site of RNA-degrading chimeras targeting SARS-CoV-2 5' untranslated region

One of the hallmarks of RNA viruses is highly structured untranslated regions (UTRs) which are often essential for viral replication, transcription, or translation. In this report, we discovered a series of coumarin derivatives that bind to a four-way RNA helix called SL5 in the 5' UTR of the SARS-CoV-2 RNA genome. To locate the binding site, we developed a sequencing-based method namely cgSHAPE-seq, in which an acylating probe was directed to crosslink with the 2'-OH group of ribose at the binding site to create read-through mutations during reverse transcription. cgSHAPE-seq unambiguously determined a bulged G in SL5 as the primary binding site, which was validated through mutagenesis and in vitro binding experiments. The coumarin derivatives were further used as a warhead in designing RNA-degrading chimeras to reduce viral RNA expression levels. The optimized RNA-degrading chimera C64 inhibited live virus replication in lung epithelial carcinoma cells.

CParty: hierarchically constrained partition function of RNA pseudoknots

MOTIVATION

Biologically relevant RNA secondary structures are routinely predicted by efficient dynamic programming algorithms that minimize their free energy. Starting from such algorithms, one can devise partition function algorithms, which enable stochastic perspectives on RNA structure ensembles. As the most prominent example, McCaskill's partition function algorithm is derived from pseudoknot-free energy minimization. While this algorithm became hugely successful for the analysis of pseudoknot-free RNA structure ensembles, as of yet there exists only one pseudoknotted partition function implementation, which covers only simple pseudoknots and comes with a borderline-prohibitive complexity of O(n5) in the RNA length n.

RESULTS

Here, we develop a partition function algorithm corresponding to the hierarchical pseudoknot prediction of HFold, which performs exact optimization in a realistic pseudoknot energy model. In consequence, our algorithm CParty carries over HFold's advantages over classical pseudoknot prediction in characterizing the Boltzmann ensemble at equilibrium. Given an RNA sequence S and a pseudoknot-free structure G, CParty computes the partition function over all possibly pseudoknotted density-2 structures G∪G' of S that extend the fixed G by a disjoint pseudoknot-free structure G'. Thus, CParty follows the common hypothesis of hierarchical pseudoknot formation, where pseudoknots form as tertiary contacts only after a first pseudoknot-free "core" G and we call the computed partition function hierarchically constrained (by G). Like HFold, the dynamic programming algorithm CParty is very efficient, achieving the low complexity of the pseudoknot-free algorithm, i.e. cubic time and quadratic space. Finally, by computing pseudoknotted ensemble energies, we unveil kinetics features of a therapeutic target in SARS-CoV-2.

AVAILABILITY AND IMPLEMENTATION

CParty is available at https://github.com/HosnaJabbari/CParty.

C→U transition biases in SARS-CoV-2: still rampant 4 years from the start of the COVID-19 pandemic

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the pandemic and post-pandemic periods has been characterized by rapid adaptive changes that confer immune escape and enhanced human-to-human transmissibility. Sequence change is additionally marked by an excess number of C→U transitions suggested as being due to host-mediated genome editing. To investigate how these influence the evolutionary trajectory of SARS-CoV-2, 2,000 high-quality, coding complete genome sequences of SARS-CoV-2 variants collected pre-September 2020 and from each subsequently appearing alpha, delta, BA.1, BA.2, BA.5, XBB, EG, HK, and JN.1 lineages were downloaded from NCBI Virus in April 2024. C→U transitions were the most common substitution during the diversification of SARS-CoV-2 lineages over the 4-year observation period. A net loss of C bases and accumulation of U's occurred at a constant rate of approximately 0.2%-0.25%/decade. C→U transitions occurred in over a quarter of all sites with a C (26.5%; range 20.0%-37.2%) around five times more than observed for the other transitions (5.3%-6.8%). In contrast to an approximately random distribution of other transitions across the genome, most C→U substitutions occurred at statistically preferred sites in each lineage. However, only the most C→U polymorphic sites showed evidence for a preferred 5'U context previously associated with APOBEC 3A editing. There was a similarly weak preference for unpaired bases suggesting much less stringent targeting of RNA than mediated by A3 deaminases in DNA editing. Future functional studies are required to determine editing preferences, impacts on replication fitness in vivo of SARS-CoV-2 and other RNA viruses, and impact on host tropism.

IMPORTANCE

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the pandemic and post-pandemic periods has shown a remarkable capacity to adapt and evade human immune responses and increase its human-to-human transmissibility. The genome of SARS-CoV-2 is also increasingly scarred by the effects of multiple C→U mutations from host genome editing as a cellular defense mechanism akin to restriction factors for retroviruses. Through the analysis of large data sets of SARS-CoV-2 isolate sequences collected throughout the pandemic period and beyond, we show that C→U transitions have driven a base compositional change over time amounting to a net loss of C bases and accumulation of U's at a rate of approximately 0.2%-0.25%/decade. Most C→U substitutions occurred in the absence of the preferred upstream-base context or targeting of unpaired RNA bases previously associated with the host RNA editing protein, APOBEC 3A. The analyses provide a series of testable hypotheses that can be experimentally investigated in the future.

Dissecting the Conformational Heterogeneity of Stem-Loop Substructures of the Fifth Element in the 5'-Untranslated Region of SARS-CoV-2

Throughout the family of coronaviruses, structured RNA elements within the 5' region of the genome are highly conserved. The fifth stem-loop element from SARS-CoV-2 (5_SL5) represents an example of an RNA structural element, repeatedly occurring in coronaviruses. It contains a conserved, repetitive fold within its substructures SL5a and SL5b. We herein report the detailed characterization of the structure and dynamics of elements SL5a and SL5b that are located immediately upstream of the SARS-CoV-2 ORF1a/b start codon. Exploiting the unique ability of solution NMR methods, we show that the structures of both apical loops are modulated by structural differences in the remote parts located in their stem regions. We further integrated our high-resolution models of SL5a/b into the context of full-length 5_SL5 structures by combining different structural biology methods. Finally, we evaluated the impact of the two most common VoC mutations within 5_SL5 with respect to individual base-pair stability.

Structural basis for the participation of the SARS-CoV-2 nucleocapsid protein in the template switch mechanism and genomic RNA reorganization

The COVID-19 pandemic has resulted in a significant toll of deaths worldwide, exceeding seven million individuals, prompting intensive research efforts aimed at elucidating the molecular mechanisms underlying the pathogenesis of SARS-CoV-2 infection. Despite the rapid development of effective vaccines and therapeutic interventions, COVID-19 remains a threat to humans due to the emergence of novel variants and largely unknown long-term consequences. Among the viral proteins, the nucleocapsid protein (N) stands out as the most conserved and abundant, playing the primary role in nucleocapsid assembly and genome packaging. The N protein is promiscuous for the recognition of RNA, yet it can perform specific functions. Here, we discuss the structural basis of specificity, which is directly linked to its regulatory role. Notably, the RNA chaperone activity of N is central to its multiple roles throughout the viral life cycle. This activity encompasses double-stranded RNA (dsRNA) annealing and melting and facilitates template switching, enabling discontinuous transcription. N also promotes the formation of membrane-less compartments through liquid-liquid phase separation, thereby facilitating the congregation of the replication and transcription complex. Considering the information available regarding the catalytic activities and binding signatures of the N protein-RNA interaction, this review focuses on the regulatory role of the SARS-CoV-2 N protein. We emphasize the participation of the N protein in discontinuous transcription, template switching, and RNA chaperone activity, including double-stranded RNA melting and annealing activities.

Sarbecovirus programmed ribosome frameshift RNA element folding studied by NMR spectroscopy and comparative analyses

The programmed ribosomal frameshift (PRF) region is found in the RNA genome of all coronaviruses and shifts the ribosome reading frame through formation of a three-stem pseudoknot structure, allowing the translation of essential viral proteins. Using NMR spectroscopy, comparative sequence analyses and functional assays we show that, in the absence of the ribosome, a 123-nucleotide sequence encompassing the PRF element of SARS-CoV-2 adopts a well-defined two-stem loop structure that is conserved in all SARS-like coronaviruses. In this conformation, the attenuator hairpin and slippery site nucleotides are exposed in the first stem-loop and two pseudoknot stems are present in the second stem-loop, separated by an 8-nucleotide bulge. Formation of the third pseudoknot stem depends on pairing between bulge nucleotides and base-paired nucleotides of the upstream stem-loop, as shown by a PRF construct where residues of the upstream stem were removed, which formed the pseudoknot structure and had increased frameshifting activity in a dual-luciferase assay. The base-pair switch driving PRF pseudoknot folding was found to be conserved in several human non-SARS coronaviruses. The collective results suggest that the frameshifting pseudoknot structure of these viruses only forms transiently in the presence of the translating ribosome. These findings clarify the frameshifting mechanism in coronaviruses and can have a beneficial impact on antiviral drug discovery.

Abolished frameshifting for predicted structure-stabilizing SARS-CoV-2 mutants: implications to alternative conformations and their statistical structural analyses

The SARS-CoV-2 frameshifting element (FSE) has been intensely studied and explored as a therapeutic target for coronavirus diseases, including COVID-19. Besides the intriguing virology, this small RNA is known to adopt many length-dependent conformations, as verified by multiple experimental and computational approaches. However, the role these alternative conformations play in the frameshifting mechanism and how to quantify this structural abundance has been an ongoing challenge. Here, we show by DMS and dual-luciferase functional assays that previously predicted FSE mutants (using the RAG graph theory approach) suppress structural transitions and abolish frameshifting. Furthermore, correlated mutation analysis of DMS data by three programs (DREEM, DRACO, and DANCE-MaP) reveals important differences in their estimation of specific RNA conformations, suggesting caution in the interpretation of such complex conformational landscapes. Overall, the abolished frameshifting in three different mutants confirms that all alternative conformations play a role in the pathways of ribosomal transition.

SARS-CoV-2 replication and drug discovery

The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has killed millions of people and continues to wreak havoc across the globe. This sudden and deadly pandemic emphasizes the necessity for anti-viral drug development that can be rapidly administered to reduce morbidity, mortality, and virus propagation. Thus, lacking efficient anti-COVID-19 treatment, and especially given the lengthy drug development process as well as the critical death tool that has been associated with SARS-CoV-2 since its outbreak, drug repurposing (or repositioning) constitutes so far, the ideal and ready-to-go best approach in mitigating viral spread, containing the infection, and reducing the COVID-19-associated death rate. Indeed, based on the molecular similarity approach of SARS-CoV-2 with previous coronaviruses (CoVs), repurposed drugs have been reported to hamper SARS-CoV-2 replication. Therefore, understanding the inhibition mechanisms of viral replication by repurposed anti-viral drugs and chemicals known to block CoV and SARS-CoV-2 multiplication is crucial, and it opens the way for particular treatment options and COVID-19 therapeutics. In this review, we highlighted molecular basics underlying drug-repurposing strategies against SARS-CoV-2. Notably, we discussed inhibition mechanisms of viral replication, involving and including inhibition of SARS-CoV-2 proteases (3C-like protease, 3CLpro or Papain-like protease, PLpro) by protease inhibitors such as Carmofur, Ebselen, and GRL017, polymerases (RNA-dependent RNA-polymerase, RdRp) by drugs like Suramin, Remdesivir, or Favipiravir, and proteins/peptides inhibiting virus-cell fusion and host cell replication pathways, such as Disulfiram, GC376, and Molnupiravir. When applicable, comparisons with SARS-CoV inhibitors approved for clinical use were made to provide further insights to understand molecular basics in inhibiting SARS-CoV-2 replication and draw conclusions for future drug discovery research.

Untangling the pseudoknots of SARS-CoV-2: Insights into structural heterogeneity and plasticity

Since the onset of the COVID-19 pandemic, one productive area of research has focused on the intricate two- and three-dimensional structures taken on by SARS-CoV-2's RNA genome. These structures control essential viral processes, making them tempting targets for therapeutic intervention. This review focuses on two such structured regions, the frameshift stimulation element (FSE), which controls the translation of viral protein, and the 3' untranslated region (3' UTR), which is thought to regulate genome replication. For the FSE, we discuss its canonical pseudoknot's threaded and unthreaded topologies, as well as the diversity of competing two-dimensional structures formed by local and long-distance base pairing. For the 3' UTR, we review the evidence both for and against the formation of its replication-enabling pseudoknot.

Structural and biophysical dissection of RNA conformational ensembles

RNA's ability to form and interconvert between multiple secondary and tertiary structures is critical to its functional versatility and the traditional view of RNA structures as static entities has shifted towards understanding them as dynamic conformational ensembles. In this review we discuss RNA structural ensembles and their dynamics, highlighting the concept of conformational energy landscapes as a unifying framework for understanding RNA processes such as folding, misfolding, conformational changes, and complex formation. Ongoing advancements in cryo-electron microscopy and chemical probing techniques are significantly enhancing our ability to investigate multiple structures adopted by conformationally dynamic RNAs, while traditional methods such as nuclear magnetic resonance spectroscopy continue to play a crucial role in providing high-resolution, quantitative spatial and temporal information. We discuss how these methods, when used synergistically, can provide a comprehensive understanding of RNA conformational ensembles, offering new insights into their regulatory functions.

Context-dependent structure formation of hairpin motifs in bacteriophage MS2 genomic RNA

Many functions of ribonucleic acid (RNA) rely on its ability to assume specific sequence-structure motifs. Packaging signals found in certain RNA viruses are one such prominent example of functional RNA motifs. These signals are short hairpin loops that interact with coat proteins and drive viral self-assembly. As they are found in different positions along the much longer genomic RNA, the formation of their correct structure occurs as a part of a larger context. Any changes to this context can consequently lead to changes in the structure of the motifs themselves. In fact, previous studies have shown that structure and function of RNA motifs can be highly context sensitive to the flanking sequence surrounding them. However, in what ways different flanking sequences influence the structure of an RNA motif they surround has yet to be studied in detail. We focus on a hairpin-rich region of the RNA genome of bacteriophage MS2-a well-studied RNA virus with a wide potential for use in biotechnology-and systematically examine context-dependent structural stability of 14 previously identified hairpin motifs, which include putative and confirmed packaging signals. Combining secondary and tertiary RNA structure prediction of the hairpin motifs placed in different contexts, ranging from the native genomic sequence to random RNA sequences and unstructured poly-U sequences, we determine different measures of motif structural stability. In this way, we show that while some motif structures can be stable in any context, others require specific context provided by the genome. Our results demonstrate the importance of context in RNA structure formation and how changes in the flanking sequence of an RNA motif sometimes lead to drastic changes in its structure. Structural stability of a motif in different contexts could provide additional insights into its functionality as well as assist in determining whether it remains functional when intentionally placed in other contexts.

Prediction of the effects of the top 10 synonymous mutations from 26645 SARS-CoV-2 genomes of early pandemic phase

Background

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had led to a global pandemic since December 2019. SARS-CoV-2 is a single-stranded RNA virus, which mutates at a higher rate. Multiple works had been done to study nonsynonymous mutations, which change protein sequences. However, there is little study on the effects of SARS-CoV-2 synonymous mutations, which may affect viral fitness. This study aims to predict the effect of synonymous mutations on the SARS-CoV-2 genome.

Methods

A total of 26645 SARS-CoV-2 genomic sequences retrieved from Global Initiative on Sharing all Influenza Data (GISAID) database were aligned using MAFFT. Then, the mutations and their respective frequency were identified. Multiple RNA secondary structures prediction tools, namely RNAfold, IPknot++ and MXfold2 were applied to predict the effect of the mutations on RNA secondary structure and their base pair probabilities was estimated using MutaRNA. Relative synonymous codon usage (RSCU) analysis was also performed to measure the codon usage bias (CUB) of SARS-CoV-2.

Results

A total of 150 synonymous mutations were identified. The synonymous mutation identified with the highest frequency is C3037U mutation in the nsp3 of ORF1a. Of these top 10 highest frequency synonymous mutations, C913U, C3037U, U16176C and C18877U mutants show pronounced changes between wild type and mutant in all 3 RNA secondary structure prediction tools, suggesting these mutations may have some biological impact on viral fitness. These four mutations show changes in base pair probabilities. All mutations except U16176C change the codon to a more preferred codon, which may result in higher translation efficiency.

Conclusion

Synonymous mutations in SARS-CoV-2 genome may affect RNA secondary structure, changing base pair probabilities and possibly resulting in a higher translation rate. However, lab experiments are required to validate the results obtained from prediction analysis.

Evaluation of the effect of RNA secondary structure on Cas13d-mediated target RNA cleavage

The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas13d system was adapted as a powerful tool for targeting viral RNA sequences, making it a promising approach for antiviral strategies. Understanding the influence of template RNA structure on Cas13d binding and cleavage efficiency is crucial for optimizing its therapeutic potential. In this study, we investigated the effect of local RNA secondary structure on Cas13d activity. To do so, we varied the stability of a hairpin structure containing the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) target sequence, allowing us to determine the threshold RNA stability at which Cas13d activity is affected. Our results demonstrate that Cas13d possesses the ability to effectively bind and cleave highly stable RNA structures. Notably, we only observed a decrease in Cas13d activity in the case of exceptionally stable RNA hairpins with completely base-paired stems, which are rarely encountered in natural RNA molecules. A comparison of Cas13d and RNA interference (RNAi)-mediated cleavage of the same RNA targets demonstrated that RNAi is more sensitive for local target RNA structures than Cas13d. These results underscore the suitability of the CRISPR-Cas13d system for targeting viruses with highly structured RNA genomes.

Mapping the structural landscape of the yeast Ty3 retrotransposon RNA genome

Long terminal repeat (LTR)-retrotransposons are significant contributors to the evolution and diversity of eukaryotic genomes. Their RNA genomes (gRNA) serve as a template for protein synthesis and reverse transcription to a DNA copy, which can integrate into the host genome. Here, we used the SHAPE-MaP strategy to explore Ty3 retrotransposon gRNA structure in yeast and under cell-free conditions. Our study reveals the structural dynamics of Ty3 gRNA and the well-folded core, formed independently of the cellular environment. Based on the detailed map of Ty3 gRNA structure, we characterized the structural context of cis-acting sequences involved in reverse transcription and frameshifting. We also identified a novel functional sequence as a potential initiator for Ty3 gRNA dimerization. Our data indicate that the dimer is maintained by direct interaction between short palindromic sequences at the 5' ends of the two Ty3 gRNAs, resembling the model characteristic for other retroelements like HIV-1 and Ty1. This work points out a range of cell-dependent and -independent Ty3 gRNA structural changes that provide a solid background for studies on RNA structure-function relationships important for retroelement biology.

Intronic RNA secondary structural information captured for the human MYC pre-mRNA

To address the lack of intronic reads in secondary structure probing data for the human MYC pre-mRNA, we developed a method that combines spliceosomal inhibition with RNA probing and sequencing. Here, the SIRP-seq method was applied to study the secondary structure of human MYC RNAs by chemically probing HeLa cells with dimethyl sulfate in the presence of the small molecule spliceosome inhibitor pladienolide B. Pladienolide B binds to the SF3B complex of the spliceosome to inhibit intron removal during splicing, resulting in retained intronic sequences. This method was used to increase the read coverage over intronic regions of MYC. The purpose for increasing coverage across introns was to generate complete reactivity profiles for intronic sequences via the DMS-MaPseq approach. Notably, depth was sufficient for analysis by the program DRACO, which was able to deduce distinct reactivity profiles and predict multiple secondary structural conformations as well as their suggested stoichiometric abundances. The results presented here provide a new method for intronic RNA secondary structural analyses, as well as specific structural insights relevant to MYC RNA splicing regulation and therapeutic targeting.

Novel Inhibitors of SARS-CoV-2 RNA Identified through Virtual Screening

We currently lack antivirals for most human viruses. In a quest for new molecules, focusing on viral RNA, instead of viral proteins, can represent a promising strategy. In this study, new inhibitors were identified starting from a published crystal structure of the tertiary SARS-CoV-2 RNA involved in the -1 programmed ribosomal frameshift. The pseudoknot structure was refined, and a virtual screening was performed using the repository of binders to the nucleic acid library, taking into consideration RNA flexibility. Hit compounds were validated against the wild-type virus and with a dual-luciferase assay measuring the frameshift efficiency. Several active molecules were identified. Our study reveals new inhibitors of SARS-CoV-2 but also highlights the feasibility of targeting RNA starting from virtual screening, a strategy that could be broadly applied to drug development.

Targeting sgRNA N secondary structure as a way of inhibiting SARS-CoV-2 replication

SARS-CoV-2 is a betacoronavirus that causes COVID-19, a global pandemic that has resulted in many infections, deaths, and socio-economic challenges. The virus has a large positive-sense, single-stranded RNA genome of ∼30 kb, which produces subgenomic RNAs (sgRNAs) through discontinuous transcription. The most abundant sgRNA is sgRNA N, which encodes the nucleocapsid (N) protein. In this study, we probed the secondary structure of sgRNA N and a shorter model without a 3' UTR in vitro, using the SHAPE (selective 2'-hydroxyl acylation analyzed by a primer extension) method and chemical mapping with dimethyl sulfate and 1-cyclohexyl-(2-morpholinoethyl) carbodiimide metho-p-toluene sulfonate. We revealed the secondary structure of sgRNA N and its shorter variant for the first time and compared them with the genomic RNA N structure. Based on the structural information, we designed gapmers, siRNAs and antisense oligonucleotides (ASOs) to target the N protein coding region of sgRNA N. We also generated eukaryotic expression vectors containing the complete sequence of sgRNA N and used them to screen for new SARS-CoV-2 gene N expression inhibitors. Our study provides novel insights into the structure and function of sgRNA N and potential therapeutic tools against SARS-CoV-2.

Rational Design Problematics of Peptide Nucleic Acids as SARS-CoV-2 Inhibitors

The use of viral protein inhibitors has shown to be insufficiently effective in the case of highly variable SARS-CoV-2. In this work, we examined the possibility of designing agents that bind to a highly conserved region of coronavirus (+)RNA. We demonstrated that while the design of antisense RNAs is based on the complementary interaction of nitrogenous bases, it is possible to use semirigid docking methods in the case of unnatural peptide nucleic acids. The transition from N-(2-aminoethyl)glycine chain to a more conformationally rigid piperidine-containing backbone allowed us to significantly increase the affinity of structures to the target RNA.

Comparative analysis of RNA 3D structure prediction methods: towards enhanced modeling of RNA-ligand interactions

Accurate RNA structure models are crucial for designing small molecule ligands that modulate their functions. This study assesses six standalone RNA 3D structure prediction methods-DeepFoldRNA, RhoFold, BRiQ, FARFAR2, SimRNA and Vfold2, excluding web-based tools due to intellectual property concerns. We focus on reproducing the RNA structure existing in RNA-small molecule complexes, particularly on the ability to model ligand binding sites. Using a comprehensive set of RNA structures from the PDB, which includes diverse structural elements, we found that machine learning (ML)-based methods effectively predict global RNA folds but are less accurate with local interactions. Conversely, non-ML-based methods demonstrate higher precision in modeling intramolecular interactions, particularly with secondary structure restraints. Importantly, ligand-binding site accuracy can remain sufficiently high for practical use, even if the overall model quality is not optimal. With the recent release of AlphaFold 3, we included this advanced method in our tests. Benchmark subsets containing new structures, not used in the training of the tested ML methods, show that AlphaFold 3's performance was comparable to other ML-based methods, albeit with some challenges in accurately modeling ligand binding sites. This study underscores the importance of enhancing binding site prediction accuracy and the challenges in modeling RNA-ligand interactions accurately.

SHAPEwarp-web: sequence-agnostic search for structurally homologous RNA regions across databases of chemical probing data

RNA molecules perform a variety of functions in cells, many of which rely on their secondary and tertiary structures. Chemical probing methods coupled with high-throughput sequencing have significantly accelerated the mapping of RNA structures, and increasingly large datasets of transcriptome-wide RNA chemical probing data are becoming available. Analogously to what has been done for decades in the protein world, this RNA structural information can be leveraged to aid the discovery of structural similarity to a known RNA (or RNA family), which, in turn, can inform about the function of transcripts. We have previously developed SHAPEwarp, a sequence-agnostic method for the search of structurally homologous RNA segments in a database of reactivity profiles derived from chemical probing experiments. In its original implementation, however, SHAPEwarp required substantial computational resources, even for moderately sized databases, as well as significant Linux command line know-how. To address these limitations, we introduce here SHAPEwarp-web, a user-friendly web interface to rapidly query large databases of RNA chemical probing data for structurally similar RNAs. Aside from featuring a completely rewritten core, which speeds up by orders of magnitude the search inside large databases, the web server hosts several high-quality chemical probing databases across multiple species. SHAPEwarp-web is available from https://shapewarp.incarnatolab.com.

An intricate balancing act: Upstream and downstream frameshift co-regulatory elements

Targeting ribosomal frameshifting has emerged as a potential therapeutic intervention strategy against Covid-19. During ribosomal translation, a fraction of elongating ribosomes slips by one base in the 5' direction and enters a new reading frame for viral protein synthesis. Any interference with this process profoundly affects viral replication and propagation. For Covid-19, two RNA sites associated with ribosomal frameshifting for SARS-CoV-2 are positioned on the 5' and 3' of the frameshifting residues. Although much attention has been on the 3' frameshift element (FSE), the 5' stem-loop (attenuator hairpin, AH) can play a role. The formation of AH has been suggested to occur as refolding of the 3' RNA structure is triggered by ribosomal unwinding. However, the attenuation activity and the relationship between the two regions are unknown. To gain more insight into these two related viral RNAs and to further enrich our understanding of ribosomal frameshifting for SARS-CoV-2, we explore the RNA folding of both 5' and 3' regions associated with frameshifting. Using our graph-theory-based modeling tools to represent RNA secondary structures, "RAG" (RNA- As-Graphs), and conformational landscapes to analyze length-dependent conformational distributions, we show that AH coexists with the 3-stem pseudoknot of the 3' FSE (graph 3_6 in our dual graph notation) and alternative pseudoknot (graph 3_3) but less likely with other 3' FSE alternative folds (such as 3-way junction 3_5). This is because an alternative length-dependent Stem 1 (AS1) can disrupt the FSE pseudoknots and trigger other folds. In addition, we design four mutants for long lengths that stabilize or disrupt AH, AS1 or FSE pseudoknot to illustrate the deduced AH/AS1 roles and favor the 3_5, 3_6 or stem-loop. These mutants further show how a strengthened pseudoknot can result from a weakened AS1, while a dominant stem-loop occurs with a strengthened AS1. These structural and mutational insights into both ends of the FSE in SARS-CoV-2 advance our understanding of the SARS-CoV-2 frameshifting mechanism by suggesting a sequence of length-dependent folds, which in turn define potential therapeutic intervention techniques involving both elements. Our work also highlights the complexity of viral landscapes with length-dependent folds, and challenges in analyzing these multiple conformations.

The RNA secondary structure of androgen receptor-FL and V7 transcripts reveals novel regulatory regions

The androgen receptor (AR) is a ligand-dependent nuclear transcription factor belonging to the steroid hormone nuclear receptor family. Due to its roles in regulating cell proliferation and differentiation, AR is tightly regulated to maintain proper levels of itself and the many genes it controls. AR dysregulation is a driver of many human diseases including prostate cancer. Though this dysregulation often occurs at the RNA level, there are many unknowns surrounding post-transcriptional regulation of AR mRNA, particularly the role that RNA secondary structure plays. Thus, a comprehensive analysis of AR transcript secondary structure is needed. We address this through the computational and experimental analyses of two key isoforms, full length (AR-FL) and truncated (AR-V7). Here, a combination of in-cell RNA secondary structure probing experiments (targeted DMS-MaPseq) and computational predictions were used to characterize the static structural landscape and conformational dynamics of both isoforms. Additionally, in-cell assays were used to identify functionally relevant structures in the 5' and 3' UTRs of AR-FL. A notable example is a conserved stem loop structure in the 5'UTR of AR-FL that can bind to Poly(RC) Binding Protein 2 (PCBP2). Taken together, our results reveal novel features that regulate AR expression.

NMR characterization and ligand binding site of the stem-loop 2 motif from the Delta variant of SARS-CoV-2

The stem-loop 2 motif (s2m) in SARS-CoV-2 (SCoV-2) is located in the 3'-UTR. Although s2m has been reported to display characteristics of a mobile genomic element that might lead to an evolutionary advantage, its function has remained unknown. The secondary structure of the original SCoV-2 RNA sequence (Wuhan-Hu-1) was determined by NMR in late 2020, delineating the base-pairing pattern and revealing substantial differences in secondary structure compared to SARS-CoV-1 (SCoV-1). The existence of a single G29742-A29756 mismatch in the upper stem of s2m leads to its destabilization and impedes a complete NMR analysis. With Delta, a variant of concern has evolved with one mutation compared to the original sequence that replaces G29742 by U29742. We show here that this mutation results in a more defined structure at ambient temperature accompanied by a rise in melting temperature. Consequently, we were able to identify >90% of the relevant NMR resonances using a combination of selective RNA labeling and filtered 2D NOESY as well as 4D NMR experiments. We present a comprehensive NMR analysis of the secondary structure, (sub)nanosecond dynamics, and ribose conformation of s2m Delta based on heteronuclear 13C NOE and T 1 measurements and ribose carbon chemical shift-derived canonical coordinates. We further show that the G29742U mutation in Delta has no influence on the druggability of s2m compared to the Wuhan-Hu-1 sequence. With the assignment at hand, we identify the flexible regions of s2m as the primary site for small molecule binding.

Structure of the SARS-CoV-2 Frameshift Stimulatory Element with an Upstream Multibranch Loop

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) frameshift stimulatory element (FSE) is necessary for programmed -1 ribosomal frameshifting (-1 PRF) and optimized viral efficacy. The FSE has an abundance of context-dependent alternate conformations, but two of the structures most crucial to -1 PRF are an attenuator hairpin and a three-stem H-type pseudoknot structure. A crystal structure of the pseudoknot alone features three RNA stems in a helically stacked linear structure, whereas a 6.9 Å cryo-EM structure including the upstream heptameric slippery site resulted in a bend between two stems. Our previous research alluded to an extended upstream multibranch loop that includes both the attenuator hairpin and the slippery site-a conformation not previously modeled. We aim to provide further context to the SARS-CoV-2 FSE via computational and medium resolution cryo-EM approaches, by presenting a 6.1 Å cryo-EM structure featuring a linear pseudoknot structure and a dynamic upstream multibranch loop.

Tying the knot: Unraveling the intricacies of the coronavirus frameshift pseudoknot

Understanding and targeting functional RNA structures towards treatment of coronavirus infection can help us to prepare for novel variants of SARS-CoV-2 (the virus causing COVID-19), and any other coronaviruses that could emerge via human-to-human transmission or potential zoonotic (inter-species) events. Leveraging the fact that all coronaviruses use a mechanism known as -1 programmed ribosomal frameshifting (-1 PRF) to replicate, we apply algorithms to predict the most energetically favourable secondary structures (each nucleotide involved in at most one pairing) that may be involved in regulating the -1 PRF event in coronaviruses, especially SARS-CoV-2. We compute previously unknown most stable structure predictions for the frameshift site of coronaviruses via hierarchical folding, a biologically motivated framework where initial non-crossing structure folds first, followed by subsequent, possibly crossing (pseudoknotted), structures. Using mutual information from 181 coronavirus sequences, in conjunction with the algorithm KnotAli, we compute secondary structure predictions for the frameshift site of different coronaviruses. We then utilize the Shapify algorithm to obtain most stable SARS-CoV-2 secondary structure predictions guided by frameshift sequence-specific and genome-wide experimental data. We build on our previous secondary structure investigation of the singular SARS-CoV-2 68 nt frameshift element sequence, by using Shapify to obtain predictions for 132 extended sequences and including covariation information. Previous investigations have not applied hierarchical folding to extended length SARS-CoV-2 frameshift sequences. By doing so, we simulate the effects of ribosome interaction with the frameshift site, providing insight to biological function. We contribute in-depth discussion to contextualize secondary structure dual-graph motifs for SARS-CoV-2, highlighting the energetic stability of the previously identified 3_8 motif alongside the known dominant 3_3 and 3_6 (native-type) -1 PRF structures. Using a combination of thermodynamic methods and sequence covariation, our novel predictions suggest function of the attenuator hairpin via previously unknown pseudoknotted base pairing. While certain initial RNA folding is consistent, other pseudoknotted base pairs form which indicate potential conformational switching between the two structures.

Large-scale analysis of small molecule-RNA interactions using multiplexed RNA structure libraries

The large-scale analysis of small-molecule binding to diverse RNA structures is key to understanding the required interaction properties and selectivity for developing RNA-binding molecules toward RNA-targeted therapies. Here, we report a new system for performing the large-scale analysis of small molecule-RNA interactions using a multiplexed pull-down assay with RNA structure libraries. The system profiled the RNA-binding landscapes of G-clamp and thiazole orange derivatives, which recognizes an unpaired guanine base and are good probes for fluorescent indicator displacement (FID) assays, respectively. We discuss the binding preferences of these molecules based on their large-scale affinity profiles. In addition, we selected combinations of fluorescent indicators and different ranks of RNA based on the information and screened for RNA-binding molecules using FID. RNAs with high- and intermediate-rank RNA provided reliable results. Our system provides fundamental information about small molecule-RNA interactions and facilitates the discovery of novel RNA-binding molecules.

NMR Studies of Genomic RNA in 3' Untranslated Region Unveil Pseudoknot Structure that Initiates Viral RNA Replication in SARS-CoV-2

In the 3' untranslated region of the SARS-CoV-2 virus RNA genome, genomic RNA replication is initiated in the highly conserved region called 3'PK, containing three stem structures (P1pk, P2, and P5). According to one proposed mechanism, P1pk and distal P2 stems switch their structure to a pseudoknot through base-pairing, thereby initiating transcription by recruiting RNA-dependent RNA polymerase complexed with nonstructural proteins (nsp)7 and nsp8. However, experimental evidence of pseudoknot formation or structural switching is unavailable. Using SARS-CoV-2 3'PK fragments, we show that 3'PK adopted stem-loop and pseudoknot forms in a mutually exclusive manner. When P1pk and P2 formed a pseudoknot, the P5 stem, which includes a sequence at the 3' end, exited from the stem-loop structure and opened up. Interaction with the nsp7/nsp8 complex destabilized the stem-loop form but did not alter the pseudoknot form. These results suggest that the interaction between the pseudoknot and nsp7/nsp8 complex transformed the 3' end of viral genomic RNA into single-stranded RNA ready for synthesis, presenting the unique pseudoknot structure as a potential pharmacological target.

Identification of Hammerhead-variant ribozyme sequences in SARS-CoV-2

The SARS-CoV-2 RNA virus and variants, responsible for the COVID-19 pandemic has become endemic, raised a need for further understanding of the viral genome and biology. Despite vast research on SARS-CoV-2, no ribozymes have been found in the virus genome. Here we report the identification of 39 Hammerhead-variant ribozyme sequences (CoV-HHRz) in SARS-CoV-2. These sequences are highly conserved within SARS-CoV-2 variants but show large diversity among other coronaviruses. In vitro CoV-HHRz sequences possess the characteristics of typical ribozymes; cleavage is pH and ion dependent, although their activity is relatively low and Mn2+ is required for cleavage. The cleavage sites of four CoV-HHRz coincide with the breakpoint of expressed subgenomic RNA (sgRNAs) in SARS-CoV-2 transcriptome data suggesting in vivo activity. The CoV-HHRz are involved in processing sgRNAs for ORF7b, ORF 10 and ORF1ab nsp13 which are essential for viral packaging and life cycle.

Conserved structures and dynamics in 5'-proximal regions of Betacoronavirus RNA genomes

Betacoronaviruses are a genus within the Coronaviridae family of RNA viruses. They are capable of infecting vertebrates and causing epidemics as well as global pandemics in humans. Mitigating the threat posed by Betacoronaviruses requires an understanding of their molecular diversity. The development of novel antivirals hinges on understanding the key regulatory elements within the viral RNA genomes, in particular the 5'-proximal region, which is pivotal for viral protein synthesis. Using a combination of cryo-electron microscopy, atomic force microscopy, chemical probing, and computational modeling, we determined the structures of 5'-proximal regions in RNA genomes of Betacoronaviruses from four subgenera: OC43-CoV, SARS-CoV-2, MERS-CoV, and Rousettus bat-CoV. We obtained cryo-electron microscopy maps and determined atomic-resolution models for the stem-loop-5 (SL5) region at the translation start site and found that despite low sequence similarity and variable length of the helical elements it exhibits a remarkable structural conservation. Atomic force microscopy imaging revealed a common domain organization and a dynamic arrangement of structural elements connected with flexible linkers across all four Betacoronavirus subgenera. Together, these results reveal common features of a critical regulatory region shared between different Betacoronavirus RNA genomes, which may allow targeting of these RNAs by broad-spectrum antiviral therapeutics.

Unveiling hidden structural patterns in the SARS-CoV-2 genome: Computational insights and comparative analysis

SARS-CoV-2, the causative agent of COVID-19, is known to exhibit secondary structures in its 5' and 3' untranslated regions, along with the frameshifting stimulatory element situated between ORF1a and 1b. To identify additional regions containing conserved structures, we utilized a multiple sequence alignment with related coronaviruses as a starting point. We applied a computational pipeline developed for identifying non-coding RNA elements. Our pipeline employed three different RNA structural prediction approaches. We identified forty genomic regions likely to harbor structures, with ten of them showing three-way consensus substructure predictions among our predictive utilities. We conducted intracomparisons of the predictive utilities within the pipeline and intercomparisons with four previously published SARS-CoV-2 structural datasets. While there was limited agreement on the precise structure, different approaches seemed to converge on regions likely to contain structures in the viral genome. By comparing and combining various computational approaches, we can predict regions most likely to form structures, as well as a probable structure or ensemble of structures. These predictions can be used to guide surveillance, prophylactic measures, or therapeutic efforts. Data and scripts employed in this study may be found at https://doi.org/10.5281/zenodo.8298680.

RNA three-dimensional structure drives the sequence organization of potato spindle tuber viroid quasispecies

RNA viruses and viroids exist and evolve as quasispecies due to error-prone replication. Quasispecies consist of a few dominant master sequences alongside numerous variants that contribute to genetic diversity. Upon environmental changes, certain variants within quasispecies have the potential to become the dominant sequences, leading to the emergence of novel infectious strains. However, the emergence of new infectious variants remains unpredictable. Using mutant pools prepared by saturation mutagenesis of selected stem and loop regions, our study of potato spindle tuber viroid (PSTVd) demonstrates that mutants forming local three-dimensional (3D) structures similar to the wild type (WT) are more likely to accumulate in PSTVd quasispecies. The selection mechanisms underlying this biased accumulation are likely associated with cell-to-cell movement and long-distance trafficking. Moreover, certain trafficking-defective PSTVd mutants can be spread by functional sister genomes in the quasispecies. Our study reveals that the RNA 3D structure of stems and loops constrains the evolution of viroid quasispecies. Mutants with a structure similar to WT have a higher likelihood of being maintained within the quasispecies and can potentially give rise to novel infectious variants. These findings emphasize the potential of targeting RNA 3D structure as a more robust approach to defend against viroid infections.

Structural Landscape of nsp Coding Genomic Regions of SARS-CoV-2-ssRNA Genome: A Structural Genomics Approach Toward Identification of Druggable Genome, Ligand-Binding Pockets, and Structure-Based Druggability

SARS-CoV-2 has a single-stranded RNA genome (+ssRNA), and synthesizes structural and non-structural proteins (nsps). All 16 nsp are synthesized from the ORF1a, and ORF1b regions associated with different life cycle preprocesses, including replication. The regions of ORF1a synthesizes nsp1 to 11, and ORF1b synthesizes nsp12 to 16. In this paper, we have predicted the secondary structure conformations, entropy & mountain plots, RNA secondary structure in a linear fashion, and 3D structure of nsp coding genes of the SARS-CoV-2 genome. We have also analyzed the A, T, G, C, A+T, and G+C contents, GC-profiling of these genes, showing the range of the GC content from 34.23 to 48.52%. We have observed that the GC-profile value of the nsp coding genomic regions was less (about 0.375) compared to the whole genome (about 0.38). Additionally, druggable pockets were identified from the secondary structure-guided 3D structural conformations. For secondary structure generation of all the nsp coding genes (nsp 1-16), we used a recent algorithm-based tool (deep learning-based) along with the conventional algorithms (centroid and MFE-based) to develop secondary structural conformations, and we found stem-loop, multi-branch loop, pseudoknot, and the bulge structural components, etc. The 3D model shows bound and unbound forms, branched structures, duplex structures, three-way junctions, four-way junctions, etc. Finally, we identified binding pockets of nsp coding genes which will help as a fundamental resource for future researchers to develop RNA-targeted therapeutics using the druggable genome.

Abolished frameshifting for predicted structure-stabilizing SARS-CoV-2 mutants: Implications to alternative conformations and their statistical structural analyses

The SARS-CoV-2 frameshifting element (FSE) has been intensely studied and explored as a therapeutic target for coronavirus diseases including COVID-19. Besides the intriguing virology, this small RNA is known to adopt many length-dependent conformations, as verified by multiple experimental and computational approaches. However, the role these alternative conformations play in the frameshifting mechanism and how to quantify this structural abundance has been an ongoing challenge. Here, we show by DMS and dual-luciferase functional assays that previously predicted FSE mutants (using the RAG graph theory approach) suppress structural transitions and abolish frameshifting. Furthermore, correlated mutation analysis of DMS data by three programs (DREEM, DRACO, and DANCE-MaP) reveals important differences in their estimation of specific RNA conformations, suggesting caution in the interpretation of such complex conformational landscapes. Overall, the abolished frameshifting in three different mutants confirms that all alternative conformations play a role in the pathways of ribosomal transition.

RNAvigate: efficient exploration of RNA chemical probing datasets

Chemical probing technologies enable high-throughput examination of diverse structural features of RNA, including local nucleotide flexibility, RNA secondary structure, protein and ligand binding, through-space interaction networks, and multistate structural ensembles. Deep understanding of RNA structure-function relationships typically requires evaluating a system under structure- and function-altering conditions, linking these data with additional information, and visualizing multilayered relationships. Current platforms lack the broad accessibility, flexibility and efficiency needed to iterate on integrative analyses of these diverse, complex data. Here, we share the RNA visualization and graphical analysis toolset RNAvigate, a straightforward and flexible Python library that automatically parses 21 standard file formats (primary sequence annotations, per- and internucleotide data, and secondary and tertiary structures) and outputs 18 plot types. RNAvigate enables efficient exploration of nuanced relationships between multiple layers of RNA structure information and across multiple experimental conditions. Compatibility with Jupyter notebooks enables nonburdensome, reproducible, transparent and organized sharing of multistep analyses and data visualization strategies. RNAvigate simplifies and accelerates discovery and characterization of RNA-centric functions in biology.

Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses

Coronavirus genomes sequester their start codons within stem-loop 5 (SL5), a structured, 5' genomic RNA element. In most alpha- and betacoronaviruses, the secondary structure of SL5 is predicted to contain a four-way junction of helical stems, some of which are capped with UUYYGU hexaloops. Here, using cryogenic electron microscopy (cryo-EM) and computational modeling with biochemically determined secondary structures, we present three-dimensional structures of SL5 from six coronaviruses. The SL5 domain of betacoronavirus severe-acute-respiratory-syndrome-related coronavirus 2 (SARS-CoV-2), resolved at 4.7 Å resolution, exhibits a T-shaped structure, with its UUYYGU hexaloops at opposing ends of a coaxial stack, the T's "arms." Further analysis of SL5 domains from SARS-CoV-1 and MERS (7.1 and 6.4 to 6.9 Å resolution, respectively) indicate that the junction geometry and inter-hexaloop distances are conserved features across these human-infecting betacoronaviruses. The MERS SL5 domain displays an additional tertiary interaction, which is also observed in the non-human-infecting betacoronavirus BtCoV-HKU5 (5.9 to 8.0 Å resolution). SL5s from human-infecting alphacoronaviruses, HCoV-229E and HCoV-NL63 (6.5 and 8.4 to 9.0 Å resolution, respectively), exhibit the same coaxial stacks, including the UUYYGU-capped arms, but with a phylogenetically distinct crossing angle, an X-shape. As such, all SL5 domains studied herein fold into stable tertiary structures with cross-genus similarities and notable differences, with implications for potential protein-binding modes and therapeutic targets.

RNA structure: implications in viral infections and neurodegenerative diseases

RNA is an intermediary between DNA and protein, a catalyzer of biochemical reactions, and a regulator of genes and transcripts. RNA structures are essential for complicated functions. Recent years have witnessed rapid advancements in RNA secondary structure probing techniques. These technological strides provided comprehensive insights into RNA structures, which significantly contributed to our understanding of diverse cellular regulatory processes, including gene regulation, epigenetic regulation, and post-transactional regulation. Meanwhile, they have facilitated the creation of therapeutic tools for tackling human diseases. Despite their therapeutic applications, RNA structure probing methods also offer a promising avenue for exploring the mechanisms of human diseases, potentially providing the key to overcoming existing research constraints and obtaining the in-depth information necessary for a deeper understanding of disease mechanisms.

2'-OH as a universal handle for studying intracellular RNAs

RNA plays pivotal roles in most cellular processes, serving as both the traditional carrier of genetic information and as a key regulator of cellular functions. The advent of chemical technologies has contributed critically to the analysis of cellular RNA structures, functions, and interactions. Many of these methods and molecules involve the utilization of chemically reactive handles in RNAs, either introduced externally or inherent within the polymer itself. Among these handles, the 2'-hydroxyl (2'-OH) group has emerged as an exceptionally well-suited and general chemical moiety for the modification and profiling of RNAs in intracellular studies. In this review, we provide an overview of the recent advancements in intracellular applications of acylation at the 2'-OH group of RNA. We outline progress made in probing RNA structure and interactomes, controlling RNA function, RNA imaging, and analyzing RNA-small molecule interactions, all achieved in living cells through this simple chemical handle on the biopolymer.

Decoding the genome of SARS-CoV-2: a pathway to drug development through translation inhibition

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the coronavirus disease 2019 (COVID-19) pandemic and is continuously spreading globally. The continuous emergence of new SARS-CoV-2 variants keeps posing threats, highlighting the need for fast-acting, mutation-resistant broad-spectrum therapeutics. Protein translation is vital for SARS-CoV-2 replication, producing early non-structural proteins for RNA replication and transcription, and late structural proteins for virion assembly. Targeted blocking of viral protein translation is thus a potential approach to developing effective anti-SARS-CoV-2 drugs. SARS-CoV-2, as an obligate parasite, utilizes the host's translation machinery. Translation-blocking strategies that target the SARS-CoV-2 mRNA, especially those that target its conserved elements are generally preferred. In this review, we discuss the current understanding of SARS-CoV-2 translation, highlighting the important conserved motifs and structures involved in its regulation. We also discuss the current strategies for blocking SARS-CoV-2 translation through viral RNA degradation or RNA element dysfunction.

Coronavirus takeover of host cell translation and intracellular antiviral response: a molecular perspective

Coronaviruses are a group of related RNA viruses that cause respiratory diseases in humans and animals. Understanding the mechanisms of translation regulation during coronaviral infections is critical for developing antiviral therapies and preventing viral spread. Translation of the viral single-stranded RNA genome in the host cell cytoplasm is an essential step in the life cycle of coronaviruses, which affects the cellular mRNA translation landscape in many ways. Here we discuss various viral strategies of translation control, including how members of the Betacoronavirus genus shut down host cell translation and suppress host innate immune functions, as well as the role of the viral non-structural protein 1 (Nsp1) in the process. We also outline the fate of viral RNA, considering stress response mechanisms triggered in infected cells, and describe how unique viral RNA features contribute to programmed ribosomal -1 frameshifting, RNA editing, and translation shutdown evasion.

Discovery of RNA secondary structural motifs using sequence-ordered thermodynamic stability and comparative sequence analysis

Major advances in RNA secondary structural motif prediction have been achieved in the last few years; however, few methods harness the predictive power of multiple approaches to deliver in-depth characterizations of local RNA motifs and their potential functionality. Additionally, most available methods do not predict RNA pseudoknots. This work combines complementary bioinformatic systems into one robust discovery pipeline where: •RNA sequences are folded to search for thermodynamically favorable motifs utilizing ScanFold.•Motifs are expanded and refolded into alternate pseudoknot conformations by Knotty/Iterative HFold.•All conformations are evaluated for covariance via the cm-builder pipeline (Infernal and R-scape).

RNA target highlights in CASP15: Evaluation of predicted models by structure providers

The first RNA category of the Critical Assessment of Techniques for Structure Prediction competition was only made possible because of the scientists who provided experimental structures to challenge the predictors. In this article, these scientists offer a unique and valuable analysis of both the successes and areas for improvement in the predicted models. All 10 RNA-only targets yielded predictions topologically similar to experimentally determined structures. For one target, experimentalists were able to phase their x-ray diffraction data by molecular replacement, showing a potential application of structure predictions for RNA structural biologists. Recommended areas for improvement include: enhancing the accuracy in local interaction predictions and increased consideration of the experimental conditions such as multimerization, structure determination method, and time along folding pathways. The prediction of RNA-protein complexes remains the most significant challenge. Finally, given the intrinsic flexibility of many RNAs, we propose the consideration of ensemble models.

Highly Potent Antisense Oligonucleotides Locked Nucleic Acid Gapmers Targeting the SARS-CoV-2 RNA Genome

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused the current worldwide pandemic and the associated coronavirus disease 2019 with potentially lethal outcome. Although effective vaccines strongly contributed to reduce disease severity, establishing a toolbox to control current and newly emerging coronaviruses of epidemic concern requires the development of novel therapeutic compounds, to treat severely infected individuals and to prevent virus transmission. Here we present a therapeutic strategy targeting the SARS-CoV-2 RNA genome using antisense oligonucleotides (ASOs). We demonstrate that selected locked nucleic acid gapmers have the potency to reduce the in vitro intracellular viral load by up to 96%. Our promising results strongly support the case for further development of our preselected ASOs as therapeutic or prophylactic antiviral agents.

RNA tertiary structure prediction in CASP15 by the GeneSilico group: Folding simulations based on statistical potentials and spatial restraints

Ribonucleic acid (RNA) molecules serve as master regulators of cells by encoding their biological function in the ribonucleotide sequence, particularly their ability to interact with other molecules. To understand how RNA molecules perform their biological tasks and to design new sequences with specific functions, it is of great benefit to be able to computationally predict how RNA folds and interacts in the cellular environment. Our workflow for computational modeling of the 3D structures of RNA and its interactions with other molecules uses a set of methods developed in our laboratory, including MeSSPredRNA for predicting canonical and non-canonical base pairs, PARNASSUS for detecting remote homology based on comparisons of sequences and secondary structures, ModeRNA for comparative modeling, the SimRNA family of programs for modeling RNA 3D structure and its complexes with other molecules, and QRNAS for model refinement. In this study, we present the results of testing this workflow in predicting RNA 3D structures in the CASP15 experiment. The overall high score of the computational models predicted by our group demonstrates the robustness of our workflow and its individual components in terms of predicting RNA 3D structures of acceptable quality that are close to the target structures. However, the variance in prediction quality is still quite high, and the results are still too far from the level of protein 3D structure predictions. This exercise led us to consider several improvements, especially to better predict and enforce stacking interactions and non-canonical base pairs.