Modelling the structures of frameshift-stimulatory pseudoknots from representative bat coronaviruses.

Coronaviruses (CoVs) use -1 programmed ribosomal frameshifting stimulated by RNA pseudoknots in the viral genome to control expression of enzymes essential for replication, making CoV pseudoknots a promising target for anti-coronaviral drugs. Bats represent one of the largest reservoirs of CoVs and are the ultimate source of most CoVs infecting humans, including those causing SARS, MERS, and COVID-19. However, the structures of bat-CoV frameshift-stimulatory pseudoknots remain largely unexplored. Here we use a combination of blind structure prediction followed by all-atom molecular dynamics simulations to model the structures of eight pseudoknots that, together with the SARS-CoV-2 pseudoknot, are representative of the range of pseudoknot sequences in bat CoVs. We find that they all share some key qualitative features with the pseudoknot from SARS-CoV-2, notably the presence of conformers with two distinct fold topologies differing in whether or not the 5' end of the RNA is threaded through a junction, and similar conformations for stem 1. However, they differed in the number of helices present, with half sharing the 3-helix architecture of the SARS-CoV-2 pseudoknot but two containing 4 helices and two others only 2. These structure models should be helpful for future work studying bat-CoV pseudoknots as potential therapeutic targets.

Evolution of coronavirus frameshifting elements: Competing stem networks explain conservation and variability.

The frameshifting RNA element (FSE) in coronaviruses (CoVs) regulates the programmed -1 ribosomal frameshift (-1 PRF) mechanism common to many viruses. The FSE is of particular interest as a promising drug candidate. Its associated pseudoknot or stem loop structure is thought to play a large role in frameshifting and thus viral protein production. To investigate the FSE structural evolution, we use our graph theory-based methods for representing RNA secondary structures in the RNA-As-Graphs (RAG) framework to calculate conformational landscapes of viral FSEs with increasing sequence lengths for representative 10 Alpha and 13 Beta-CoVs. By following length-dependent conformational changes, we show that FSE sequences encode many possible competing stems which in turn favor certain FSE topologies, including a variety of pseudoknots, stem loops, and junctions. We explain alternative competing stems and topological FSE changes by recurring patterns of mutations. At the same time, FSE topology robustness can be understood by shifted stems within different sequence contexts and base pair coevolution. We further propose that the topology changes reflected by length-dependent conformations contribute to tuning the frameshifting efficiency. Our work provides tools to analyze virus sequence/structure correlations, explains how sequence and FSE structure have evolved for CoVs, and provides insights into potential mutations for therapeutic applications against a broad spectrum of CoV FSEs by targeting key sequence/structural transitions.

Predicting 3D structures and stabilities for complex RNA pseudoknots in ion solutions.

RNA pseudoknots are a kind of important tertiary motif, and the structures and stabilities of pseudoknots are generally critical to the biological functions of RNAs with the motifs. In this work, we have carefully refined our previously developed coarse-grained model with salt effect through involving a new coarse-grained force field and a replica-exchange Monte Carlo algorithm, and employed the model to predict structures and stabilities of complex RNA pseudoknots in ion solutions beyond minimal H-type pseudoknots. Compared with available experimental data, the newly refined model can successfully predict 3D structures from sequences for the complex RNA pseudoknots including SARS-CoV-2 programming-1 ribosomal frameshifting element and Zika virus xrRNA, and can reliably predict the thermal stabilities of RNA pseudoknots with various sequences and lengths over broad ranges of monovalent/divalent salts. In addition, for complex pseudoknots including SARS-CoV-2 frameshifting element, our analyses show that their thermally unfolding pathways are mainly dependent on the relative stabilities of unfolded intermediate states, in analogy to those of minimal H-type pseudoknots.

RPflex: A Coarse-Grained Network Model for RNA Pocket Flexibility Study.

RNA regulates various biological processes, such as gene regulation, RNA splicing, and intracellular signal transduction. RNA's conformational dynamics play crucial roles in performing its diverse functions. Thus, it is essential to explore the flexibility characteristics of RNA, especially pocket flexibility. Here, we propose a computational approach, RPflex, to analyze pocket flexibility using the coarse-grained network model. We first clustered 3154 pockets into 297 groups by similarity calculation based on the coarse-grained lattice model. Then, we introduced the flexibility score to quantify the flexibility by global pocket features. The results show strong correlations between the flexibility scores and root-mean-square fluctuation (RMSF) values, with Pearson correlation coefficients of 0.60, 0.76, and 0.53 in Testing Sets I-III. Considering both flexibility score and network calculations, the Pearson correlation coefficient was increased to 0.71 in flexible pockets on Testing Set IV. The network calculations reveal that the long-range interaction changes contributed most to flexibility. In addition, the hydrogen bonds in the base-base interactions greatly stabilize the RNA structure, while backbone interactions determine RNA folding. The computational analysis of pocket flexibility could facilitate RNA engineering for biological or medical applications.

Shapify: Paths to SARS-CoV-2 frameshifting pseudoknot.

Multiple coronaviruses including MERS-CoV causing Middle East Respiratory Syndrome, SARS-CoV causing SARS, and SARS-CoV-2 causing COVID-19, use a mechanism known as -1 programmed ribosomal frameshifting (-1 PRF) to replicate. SARS-CoV-2 possesses a unique RNA pseudoknotted structure that stimulates -1 PRF. Targeting -1 PRF in SARS-CoV-2 to impair viral replication can improve patients' prognoses. Crucial to developing these therapies is understanding the structure of the SARS-CoV-2 -1 PRF pseudoknot. Our goal is to expand knowledge of -1 PRF structural conformations. Following a structural alignment approach, we identify similarities in -1 PRF pseudoknots of SARS-CoV-2, SARS-CoV, and MERS-CoV. We provide in-depth analysis of the SARS-CoV-2 and MERS-CoV -1 PRF pseudoknots, including reference and noteworthy mutated sequences. To better understand the impact of mutations, we provide insight on -1 PRF pseudoknot sequence mutations and their effect on resulting structures. We introduce Shapify, a novel algorithm that given an RNA sequence incorporates structural reactivity (SHAPE) data and partial structure information to output an RNA secondary structure prediction within a biologically sound hierarchical folding approach. Shapify enhances our understanding of SARS-CoV-2 -1 PRF pseudoknot conformations by providing energetically favourable predictions that are relevant to structure-function and may correlate with -1 PRF efficiency. Applied to the SARS-CoV-2 -1 PRF pseudoknot, Shapify unveils previously unknown paths from initial stems to pseudoknotted structures. By contextualizing our work with available experimental data, our structure predictions motivate future RNA structure-function research and can aid 3-D modeling of pseudoknots.

Knotify+: Toward the Prediction of RNA H-Type Pseudoknots, Including Bulges and Internal Loops.

The accurate "base pairing" in RNA molecules, which leads to the prediction of RNA secondary structures, is crucial in order to explain unknown biological operations. Recently, COVID-19, a widespread disease, has caused many deaths, affecting humanity in an unprecedented way. SARS-CoV-2, a single-stranded RNA virus, has shown the significance of analyzing these molecules and their structures. This paper aims to create a pioneering framework in the direction of predicting specific RNA structures, leveraging syntactic pattern recognition. The proposed framework, Knotify+, addresses the problem of predicting H-type pseudoknots, including bulges and internal loops, by featuring the power of context-free grammar (CFG). We combine the grammar's advantages with maximum base pairing and minimum free energy to tackle this ambiguous task in a performant way. Specifically, our proposed methodology, Knotify+, outperforms state-of-the-art frameworks with regards to its accuracy in core stems prediction. Additionally, it performs more accurately in small sequences and presents a comparable accuracy rate in larger ones, while it requires a smaller execution time compared to well-known platforms. The Knotify+ source code and implementation details are available as a public repository on GitHub.

Cis-mediated interactions of the SARS-CoV-2 frameshift RNA alter its conformations and affect function.

The RNA genome of SARS-CoV-2 contains a frameshift stimulatory element (FSE) that allows access to an alternative reading frame through -1 programmed ribosomal frameshifting (PRF). -1PRF in the 1a/1b gene is essential for efficient viral replication and transcription of the viral genome. -1PRF efficiency relies on the presence of conserved RNA elements within the FSE. One of these elements is a three-stemmed pseudoknot, although alternative folds of the frameshift site might have functional roles as well. Here, by complementing ensemble and single-molecule structural analysis of SARS-CoV-2 frameshift RNA variants with functional data, we reveal a conformational interplay of the 5' and 3' immediate regions with the FSE and show that the extended FSE exists in multiple conformations. Furthermore, limiting the base pairing of the FSE with neighboring nucleotides can favor or impair the formation of the alternative folds, including the pseudoknot. Our results demonstrate that co-existing RNA structures can function together to fine-tune SARS-CoV-2 gene expression, which will aid efforts to design specific inhibitors of viral frameshifting.

4-Aminoquinolines modulate RNA structure and function: Pharmacophore implications of a conformationally restricted polyamine.

RNA structure plays an important role in regulating cellular function and there is a significant emerging interest in targeting RNA for drug discovery. Here we report the identification of 4-aminoquinolines as modulators of RNA structure and function. Aminoquinolines have a broad range of pharmacological activities, but their specific mechanism of action is often not fully understood. Using electrophoretic mobility shift assays and enzymatic probing we identified 4-aminoquinolines that bind the stem-loop II motif (s2m) of SARS-CoV-2 RNA site-specifically and induce dimerization. Using fluorescence-based RNA binding and T-box riboswitch functional assays we identified that hydroxychloroquine binds the T-box riboswitch antiterminator RNA element and inhibits riboswitch function. Based on its structure and riboswitch dose-response activity we identified that the antagonist activity of hydroxychloroquine is consistent with it being a conformationally restricted analog of the polyamine spermidine. Given the known role that polyamines play in RNA function, the identification of an RNA binding ligand with the pharmacophore of a conformationally restricted polyamine has significant implications for further elucidation of RNA structure-function relationships and RNA-targeted drug discovery.

Epistasis-Driven Evolution of the SARS-CoV-2 Secondary Structure.

Epistasis is an evolutionary phenomenon whereby the fitness effect of a mutation depends on the genetic background in which it arises. A key source of epistasis in an RNA molecule is its secondary structure, which contains functionally important topological motifs held together by hydrogen bonds between Watson-Crick (WC) base pairs. Here we study epistasis in the secondary structure of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by examining properties of derived alleles arising from substitution mutations at ancestral WC base-paired and unpaired (UP) sites in 15 conserved topological motifs across the genome. We uncover fewer derived alleles and lower derived allele frequencies at WC than at UP sites, supporting the hypothesis that modifications to the secondary structure are often deleterious. At WC sites, we also find lower derived allele frequencies for mutations that abolish base pairing than for those that yield G·U "wobbles," illustrating that weak base pairing can partially preserve the integrity of the secondary structure. Last, we show that WC sites under the strongest epistatic constraint reside in a three-stemmed pseudoknot motif that plays an essential role in programmed ribosomal frameshifting, whereas those under the weakest epistatic constraint are located in 3' UTR motifs that regulate viral replication and pathogenicity. Our findings demonstrate the importance of epistasis in the evolution of the SARS-CoV-2 secondary structure, as well as highlight putative structural and functional targets of different forms of natural selection.

RAFFT: Efficient prediction of RNA folding pathways using the fast Fourier transform.

We propose a novel heuristic to predict RNA secondary structure formation pathways that has two components: (i) a folding algorithm and (ii) a kinetic ansatz. This heuristic is inspired by the kinetic partitioning mechanism, by which molecules follow alternative folding pathways to their native structure, some much faster than others. Similarly, our algorithm RAFFT starts by generating an ensemble of concurrent folding pathways ending in multiple metastable structures, which is in contrast with traditional thermodynamic approaches that find single structures with minimal free energies. When we constrained the algorithm to predict only 50 structures per sequence, near-native structures were found for RNA molecules of length ≤ 200 nucleotides. Our heuristic has been tested on the coronavirus frameshifting stimulation element (CFSE): an ensemble of 68 distinct structures allowed us to produce complete folding kinetic trajectories, whereas known methods require evaluating millions of sub-optimal structures to achieve this result. Thanks to the fast Fourier transform on which RAFFT (RNA folding Algorithm wih Fast Fourier Transform) is based, these computations are efficient, with complexity [Formula: see text].

Computational Pipeline for Reference-Free Comparative Analysis of RNA 3D Structures Applied to SARS-CoV-2 UTR Models.

RNA is a unique biomolecule that is involved in a variety of fundamental biological functions, all of which depend solely on its structure and dynamics. Since the experimental determination of crystal RNA structures is laborious, computational 3D structure prediction methods are experiencing an ongoing and thriving development. Such methods can lead to many models; thus, it is necessary to build comparisons and extract common structural motifs for further medical or biological studies. Here, we introduce a computational pipeline dedicated to reference-free high-throughput comparative analysis of 3D RNA structures. We show its application in the RNA-Puzzles challenge, in which five participating groups attempted to predict the three-dimensional structures of 5'- and 3'-untranslated regions (UTRs) of the SARS-CoV-2 genome. We report the results of this puzzle and discuss the structural motifs obtained from the analysis. All simulated models and tools incorporated into the pipeline are open to scientific and academic use.

Translation of SARS-CoV-2 gRNA Is Extremely Efficient and Competitive despite a High Degree of Secondary Structures and the Presence of an uORF.

The SARS-CoV-2 infection generates up to nine different sub-genomic mRNAs (sgRNAs), in addition to the genomic RNA (gRNA). The 5'UTR of each viral mRNA shares the first 75 nucleotides (nt.) at their 5'end, called the leader, but differentiates by a variable sequence (0 to 190 nt. long) that follows the leader. As a result, each viral mRNA has its own specific 5'UTR in term of length, RNA structure, uORF and Kozak context; each one of these characteristics could affect mRNA expression. In this study, we have measured and compared translational efficiency of each of the ten viral transcripts. Our data show that most of them are very efficiently translated in all translational systems tested. Surprisingly, the gRNA 5'UTR, which is the longest and the most structured, was also the most efficient to initiate translation. This property is conserved in the 5'UTR of SARS-CoV-1 but not in MERS-CoV strain, mainly due to the regulation imposed by the uORF. Interestingly, the translation initiation mechanism on the SARS-CoV-2 gRNA 5'UTR requires the cap structure and the components of the eIF4F complex but showed no dependence in the presence of the poly(A) tail in vitro. Our data strongly suggest that translation initiation on SARS-CoV-2 mRNAs occurs via an unusual cap-dependent mechanism.

Length-dependent motions of SARS-CoV-2 frameshifting RNA pseudoknot and alternative conformations suggest avenues for frameshifting suppression.

The SARS-CoV-2 frameshifting element (FSE), a highly conserved mRNA region required for correct translation of viral polyproteins, defines an excellent therapeutic target against Covid-19. As discovered by our prior graph-theory analysis with SHAPE experiments, the FSE adopts a heterogeneous, length-dependent conformational landscape consisting of an assumed 3-stem H-type pseudoknot (graph motif 3_6), and two alternative motifs (3_3 and 3_5). Here, for the first time, we build and simulate, by microsecond molecular dynamics, 30 models for all three motifs plus motif-stabilizing mutants at different lengths. Our 3_6 pseudoknot systems, which agree with experimental structures, reveal interconvertible L and linear conformations likely related to ribosomal pausing and frameshifting. The 3_6 mutant inhibits this transformation and could hamper frameshifting. Our 3_3 systems exhibit length-dependent stem interactions that point to a potential transition pathway connecting the three motifs during ribosomal elongation. Together, our observations provide new insights into frameshifting mechanisms and anti-viral strategies.

Exploring the multiple conformational states of RNA genome through interhelical dynamics and network analysis.

The structural variation of RNA is often very transient and can be easily missed in experiments. Molecular dynamics simulation studies along with network analysis can be an effective tool to identify prominent conformations of such dynamic biomolecular systems. Here we describe a method to effectively sample different RNA conformations at six different temperatures based on the changes in the interhelical orientations. This method gives the information about prominent states of the RNA as well as the probability of the existence of different conformations and their interconnections during the process of evolution. In the case of the SARS-CoV-2 genome, the change of prominent structures was found to be faster at 333 K as compared to higher temperatures due to the formation of the non-native base pairs. ΔΔG calculated between 288 K and 363 K are found to be 10.31 kcal/mol (88 nt) considering the contribution from the multiple states of the RNA which agrees well with the experimentally reported denaturation energy for E. coli α mRNA pseudoknot (∼16 kcal/mol, 112 nt) determined by calorimetry/UV hyperchromicity and human telomerase RNA telomerase (4.5-6.6 kcal/mol, 54 nt) determined by FRET analysis.

Recent advances in RNA structurome.

RNA structures are essential to support RNA functions and regulation in various biological processes. Recently, a range of novel technologies have been developed to decode genome-wide RNA structures and novel modes of functionality across a wide range of species. In this review, we summarize key strategies for probing the RNA structurome and discuss the pros and cons of representative technologies. In particular, these new technologies have been applied to dissect the structural landscape of the SARS-CoV-2 RNA genome. We also summarize the functionalities of RNA structures discovered in different regulatory layers-including RNA processing, transport, localization, and mRNA translation-across viruses, bacteria, animals, and plants. We review many versatile RNA structural elements in the context of different physiological and pathological processes (e.g., cell differentiation, stress response, and viral replication). Finally, we discuss future prospects for RNA structural studies to map the RNA structurome at higher resolution and at the single-molecule and single-cell level, and to decipher novel modes of RNA structures and functions for innovative applications.

Inhibition of the hexamerization of SARS-CoV-2 endoribonuclease and modeling of RNA structures bound to the hexamer.

Non-structural protein 15 (Nsp15) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) forms a homo hexamer and functions as an endoribonuclease. Here, we propose that Nsp15 activity may be inhibited by preventing its hexamerization through drug binding. We first explored the stable conformation of the Nsp15 monomer as the global free energy minimum conformation in the free energy landscape using a combination of parallel cascade selection molecular dynamics (PaCS-MD) and the Markov state model (MSM), and found that the Nsp15 monomer forms a more open conformation with larger druggable pockets on the surface. Targeting the pockets with high druggability scores, we conducted ligand docking and identified compounds that tightly bind to the Nsp15 monomer. The top poses with Nsp15 were subjected to binding free energy calculations by dissociation PaCS-MD and MSM (dPaCS-MD/MSM), indicating the stability of the complexes. One of the identified pockets, which is distinctively bound by inosine analogues, may be an alternative binding site to stabilize viral RNA binding and/or an alternative catalytic site. We constructed a stable RNA structure model bound to both UTP and alternative binding sites, providing a reasonable proposed model of the Nsp15/RNA complex.

Fast Ion-Beam Inactivation of Viruses, Where Radiation Track Structure Meets RNA Structural Biology.

Here we show an interplay between the structures present in ionization tracks and nucleocapsid RNA structural biology, using fast ion-beam inactivation of the severe acute respiratory syndrome coronavirus (SARS-CoV) virion as an example. This interplay could be a key factor in predicting dose-inactivation curves for high-energy ion-beam inactivation of virions. We also investigate the adaptation of well-established cross-section data derived from radiation interactions with water to the interactions involving the components of a virion, going beyond the density-scaling approximation developed previously. We conclude that solving one of the grand challenges of structural biology - the determination of RNA tertiary/quaternary structure - is linked to predicting ion-beam inactivation of viruses and that the two problems can be mutually informative. Indeed, our simulations show that fast ion beams have a key role to play in elucidating RNA tertiary/quaternary structure.

SHAPE-guided RNA structure homology search and motif discovery.

The rapidly growing popularity of RNA structure probing methods is leading to increasingly large amounts of available RNA structure information. This demands the development of efficient tools for the identification of RNAs sharing regions of structural similarity by direct comparison of their reactivity profiles, hence enabling the discovery of conserved structural features. We here introduce SHAPEwarp, a largely sequence-agnostic SHAPE-guided algorithm for the identification of structurally-similar regions in RNA molecules. Analysis of Dengue, Zika and coronavirus genomes recapitulates known regulatory RNA structures and identifies novel highly-conserved structural elements. This work represents a preliminary step towards the model-free search and identification of shared and conserved RNA structural features within transcriptomes.

Secondary structural ensembles of the SARS-CoV-2 RNA genome in infected cells.

SARS-CoV-2 is a betacoronavirus with a single-stranded, positive-sense, 30-kilobase RNA genome responsible for the ongoing COVID-19 pandemic. Although population average structure models of the genome were recently reported, there is little experimental data on native structural ensembles, and most structures lack functional characterization. Here we report secondary structure heterogeneity of the entire SARS-CoV-2 genome in two lines of infected cells at single nucleotide resolution. Our results reveal alternative RNA conformations across the genome and at the critical frameshifting stimulation element (FSE) that are drastically different from prevailing population average models. Importantly, we find that this structural ensemble promotes frameshifting rates much higher than the canonical minimal FSE and similar to ribosome profiling studies. Our results highlight the value of studying RNA in its full length and cellular context. The genomic structures detailed here lay groundwork for coronavirus RNA biology and will guide the design of SARS-CoV-2 RNA-based therapeutics.