Structural and functional conservation of the programmed -1 ribosomal frameshift signal of SARS coronavirus 2 (SARS-CoV-2)

CRISPR screening reveals a dependency on ribosome recycling for efficient SARS-CoV-2 programmed ribosomal frameshifting and viral replication

During translation of the genomic RNA of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus in the COVID-19 pandemic, host ribosomes undergo programmed ribosomal frameshifting (PRF) at a conserved structural element. Although PRF is essential for coronavirus replication, host factors that regulate this process have not yet been identified. Here we perform genome-wide CRISPR-Cas9 knockout screens to identify regulators of SARS-CoV-2 PRF. These screens reveal that loss of ribosome recycling factors markedly decreases frameshifting efficiency and impairs SARS-CoV-2 viral replication. Mutational studies support a model wherein efficient removal of ribosomal subunits at the ORF1a stop codon is required for frameshifting of trailing ribosomes. This dependency upon ribosome recycling is not observed with other non-pathogenic human betacoronaviruses and is likely due to the unique position of the ORF1a stop codon in the SARS clade of coronaviruses. These findings therefore uncover host factors that support efficient SARS-CoV-2 translation and replication.

Identification of and Mechanistic Insights into SARS-CoV-2 Main Protease Non-Covalent Inhibitors: An In-Silico Study

The indispensable role of the SARS-CoV-2 main protease (Mpro) in the viral replication cycle and its dissimilarity to human proteases make Mpro a promising drug target. In order to identify the non-covalent Mpro inhibitors, we performed a comprehensive study using a combined computational strategy. We first screened the ZINC purchasable compound database using the pharmacophore model generated from the reference crystal structure of Mpro complexed with the inhibitor ML188. The hit compounds were then filtered by molecular docking and predicted parameters of drug-likeness and pharmacokinetics. The final molecular dynamics (MD) simulations identified three effective candidate inhibitors (ECIs) capable of maintaining binding within the substrate-binding cavity of Mpro. We further performed comparative analyses of the reference and effective complexes in terms of dynamics, thermodynamics, binding free energy (BFE), and interaction energies and modes. The results reveal that, when compared to the inter-molecular electrostatic forces/interactions, the inter-molecular van der Waals (vdW) forces/interactions are far more important in maintaining the association and determining the high affinity. Given the un-favorable effects of the inter-molecular electrostatic interactions-association destabilization by the competitive hydrogen bond (HB) interactions and the reduced binding affinity arising from the un-compensable increase in the electrostatic desolvation penalty-we suggest that enhancing the inter-molecular vdW interactions while avoiding introducing the deeply buried HBs may be a promising strategy in future inhibitor optimization.

Structural and Functional RNA Motifs of SARS-CoV-2 and Influenza A Virus as a Target of Viral Inhibitors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the COVID-19 pandemic, whereas the influenza A virus (IAV) causes seasonal epidemics and occasional pandemics. Both viruses lead to widespread infection and death. SARS-CoV-2 and the influenza virus are RNA viruses. The SARS-CoV-2 genome is an approximately 30 kb, positive sense, 5' capped single-stranded RNA molecule. The influenza A virus genome possesses eight single-stranded negative-sense segments. The RNA secondary structure in the untranslated and coding regions is crucial in the viral replication cycle. The secondary structure within the RNA of SARS-CoV-2 and the influenza virus has been intensively studied. Because the whole of the SARS-CoV-2 and influenza virus replication cycles are dependent on RNA with no DNA intermediate, the RNA is a natural and promising target for the development of inhibitors. There are a lot of RNA-targeting strategies for regulating pathogenic RNA, such as small interfering RNA for RNA interference, antisense oligonucleotides, catalytic nucleic acids, and small molecules. In this review, we summarized the knowledge about the inhibition of SARS-CoV-2 and influenza A virus propagation by targeting their RNA secondary structure.

Multilevel thresholding satellite image segmentation using chaotic coronavirus optimization algorithm with hybrid fitness function

Image segmentation is a critical step in digital image processing applications. One of the most preferred methods for image segmentation is multilevel thresholding, in which a set of threshold values is determined to divide an image into different classes. However, the computational complexity increases when the required thresholds are high. Therefore, this paper introduces a modified Coronavirus Optimization algorithm for image segmentation. In the proposed algorithm, the chaotic map concept is added to the initialization step of the naive algorithm to increase the diversity of solutions. A hybrid of the two commonly used methods, Otsu's and Kapur's entropy, is applied to form a new fitness function to determine the optimum threshold values. The proposed algorithm is evaluated using two different datasets, including six benchmarks and six satellite images. Various evaluation metrics are used to measure the quality of the segmented images using the proposed algorithm, such as mean square error, peak signal-to-noise ratio, Structural Similarity Index, Feature Similarity Index, and Normalized Correlation Coefficient. Additionally, the best fitness values are calculated to demonstrate the proposed method's ability to find the optimum solution. The obtained results are compared to eleven powerful and recent metaheuristics and prove the superiority of the proposed algorithm in the image segmentation problem.

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.

Data quality assurance, model validation, and data sharing for biomolecular structures from small-angle scattering

Key to small-angle scattering (SAS) maturing and becoming a mainstream structural biology technique was the work done by the SAS community to establish standards for data quality, model validation and data sharing. Through a consultative process spanning more than a decade and a half, guidelines for publication have been established that include criteria for evaluating data quality and for model validation. In this process gaps were identified that stimulated innovation and development of new tools, for example new measures of model ambiguity and of the goodness-of-fit of a model to SAS data that complement the traditional global fit parameter χ². The need for a global repository for biomolecular SAS data and models was identified and the SASBDB was established as a searchable, curated, freely accessible, downloadable database of experimental data, experimental conditions, sample details, derived models, and their fit to the data. Importantly, the SASBDB uses a common dictionary format that supports archiving of structures solved using integrative methods to support seamless data exchange with a federated system of public databanks that includes the world-wide Protein Data Bank (wwPDB) as the major repository for structural biology. Thus, biomolecular SAS is now well-positioned to achieve its full potential as a mainstream structural biology technique contributing at the frontier of integrative structural biology and meeting "best practice" standards for data quality assurance and data sharing.

Nucleoside Analogs and Perylene Derivatives Modulate Phase Separation of SARS-CoV-2 N Protein and Genomic RNA In Vitro

The life cycle of severe acute respiratory syndrome coronavirus 2 includes several steps that are supposedly mediated by liquid-liquid phase separation (LLPS) of the viral nucleocapsid protein (N) and genomic RNA. To facilitate the rational design of LLPS-targeting therapeutics, we modeled N-RNA biomolecular condensates in vitro and analyzed their sensitivity to several small-molecule antivirals. The model condensates were obtained and visualized under physiological conditions using an optimized RNA sequence enriched with N-binding motifs. The antivirals were selected based on their presumed ability to compete with RNA for specific N sites or interfere with non-specific pi-pi/cation-pi interactions. The set of antivirals included fleximers, 5'-norcarbocyclic nucleoside analogs, and perylene-harboring nucleoside analogs as well as non-nucleoside amphiphilic and hydrophobic perylene derivatives. Most of these antivirals enhanced the formation of N-RNA condensates. Hydrophobic perylene derivatives and 5'-norcarbocyclic derivatives caused up to 50-fold and 15-fold enhancement, respectively. Molecular modeling data argue that hydrophobic compounds do not hamper specific N-RNA interactions and may promote non-specific ones. These findings shed light on the determinants of potent small-molecule modulators of viral LLPS.

Altered tRNA dynamics during translocation on slippery mRNA as determinant of spontaneous ribosome frameshifting

When reading consecutive mRNA codons, ribosomes move by exactly one triplet at a time to synthesize a correct protein. Some mRNA tracks, called slippery sequences, are prone to ribosomal frameshifting, because the same tRNA can read both 0- and –1-frame codon. Using smFRET we show that during EF-G-catalyzed translocation on slippery sequences a fraction of ribosomes spontaneously switches from rapid, accurate translation to a slow, frameshifting-prone translocation mode where the movements of peptidyl- and deacylated tRNA become uncoupled. While deacylated tRNA translocates rapidly, pept-tRNA continues to fluctuate between chimeric and posttranslocation states, which slows down the re-locking of the small ribosomal subunit head domain. After rapid release of deacylated tRNA, pept-tRNA gains unconstrained access to the –1-frame triplet, resulting in slippage followed by recruitment of the –1-frame aa-tRNA into the A site. Our data show how altered choreography of tRNA and ribosome movements reduces the translation fidelity of ribosomes translocating in a slow mode.

Biomotors, viral assembly, and RNA nanobiotechnology: Current achievements and future directions

The International Society of RNA Nanotechnology and Nanomedicine (ISRNN) serves to further the development of a wide variety of functional nucleic acids and other related nanotechnology platforms. To aid in the dissemination of the most recent advancements, a biennial discussion focused on biomotors, viral assembly, and RNA nanobiotechnology has been established where international experts in interdisciplinary fields such as structural biology, biophysical chemistry, nanotechnology, cell and cancer biology, and pharmacology share their latest accomplishments and future perspectives. The results summarized here highlight advancements in our understanding of viral biology and the structure-function relationship of frame-shifting elements in genomic viral RNA, improvements in the predictions of SHAPE analysis of 3D RNA structures, and the understanding of dynamic RNA structures through a variety of experimental and computational means. Additionally, recent advances in the drug delivery, vaccine design, nanopore technologies, biomotor and biomachine development, DNA packaging, RNA nanotechnology, and drug delivery are included in this critical review. We emphasize some of the novel accomplishments, major discussion topics, and present current challenges and perspectives of these emerging fields.

Multilevel segmentation of 2D and volumetric medical images using hybrid Coronavirus Optimization Algorithm

Medical image segmentation is a crucial step in Computer-Aided Diagnosis systems, where accurate segmentation is vital for perfect disease diagnoses. This paper proposes a multilevel thresholding technique for 2D and 3D medical image segmentation using Otsu and Kapur's entropy methods as fitness functions to determine the optimum threshold values. The proposed algorithm applies the hybridization concept between the recent Coronavirus Optimization Algorithm (COVIDOA) and Harris Hawks Optimization Algorithm (HHOA) to benefit from both algorithms' strengths and overcome their limitations. The improved performance of the proposed algorithm over COVIDOA and HHOA algorithms is demonstrated by solving 5 test problems from IEEE CEC 2019 benchmark problems. Medical image segmentation is tested using two groups of images, including 2D medical images and volumetric (3D) medical images, to demonstrate its superior performance. The utilized test images are from different modalities such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and X-ray images. The proposed algorithm is compared with seven well-known metaheuristic algorithms, where the performance is evaluated using four different metrics, including the best fitness values, Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Normalized Correlation Coefficient (NCC). The experimental results demonstrate the superior performance of the proposed algorithm in terms of convergence to the global optimum and making a good balance between exploration and exploitation properties. Moreover, the quality of the segmented images using the proposed algorithm at different threshold levels is better than the other methods according to PSNR, SSIM, and NCC values. Additionally, the Wilcoxon rank-sum test is conducted to prove the statistical significance of the proposed algorithm.

Alternative RNA Conformations: Companion or Combatant

RNA molecules, in one form or another, are involved in almost all aspects of cell physiology, as well as in disease development. The diversity of the functional roles of RNA comes from its intrinsic ability to adopt complex secondary and tertiary structures, rivaling the diversity of proteins. The RNA molecules form dynamic ensembles of many interconverting conformations at a timescale of seconds, which is a key for understanding how they execute their cellular functions. Given the crucial role of RNAs in various cellular processes, we need to understand the RNA molecules from a structural perspective. Central to this review are studies aimed at revealing the regulatory role of conformational equilibria in RNA in humans to understand genetic diseases such as cancer and neurodegenerative diseases, as well as in pathogens such as bacteria and viruses so as to understand the progression of infectious diseases. Furthermore, we also summarize the prior studies on the use of RNA structures as platforms for the rational design of small molecules for therapeutic applications.

Distinct Molecular Mechanisms Characterizing Pathogenesis of SARS-CoV-2

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has continued for over 2 years, following the outbreak of coronavirus-19 (COVID-19) in 2019. It has resulted in enormous casualties and severe economic crises. The rapid development of vaccines and therapeutics against SARS-CoV-2 has helped slow the spread. In the meantime, various mutations in the SARS-CoV-2 have emerged to evade current vaccines and therapeutics. A better understanding of SARS-CoV-2 pathogenesis is a prerequisite for developing efficient, advanced vaccines and therapeutics. Since the outbreak of COVID-19, a tremendous amount of research has been conducted to unveil SARSCoV-2 pathogenesis, from clinical observations to biochemical analysis at the molecular level upon viral infection. In this review, we discuss the molecular mechanisms of SARS-CoV-2 propagation and pathogenesis, with an update on recent advances.

A genetically encoded BRET-based SARS-CoV-2 Mpro protease activity sensor

The main protease, Mpro, is critical for SARS-CoV-2 replication and an appealing target for designing anti-SARS-CoV-2 agents. Therefore, there is a demand for the development of improved sensors to monitor its activity. Here, we report a pair of genetically encoded, bioluminescence resonance energy transfer (BRET)-based sensors for detecting Mpro proteolytic activity in live cells as well as in vitro. The sensors were generated by sandwiching peptides containing the Mpro N-terminal autocleavage sites, either AVLQSGFR (short) or KTSAVLQSGFRKME (long), in between the mNeonGreen and NanoLuc proteins. Co-expression of the sensors with Mpro in live cells resulted in their cleavage while mutation of the critical C145 residue (C145A) in Mpro completely abrogated their cleavage. Additionally, the sensors recapitulated the inhibition of Mpro by the well-characterized pharmacological agent GC376. Further, in vitro assays with the BRET-based Mpro sensors revealed a molecular crowding-mediated increase in the rate of Mpro activity and a decrease in the inhibitory potential of GC376. The sensors developed here will find direct utility in studies related to drug discovery targeting the SARS-CoV-2 Mpro and functional genomics application to determine the effect of sequence variation in Mpro.

Variant-Specific Analysis Reveals a Novel Long-Range RNA-RNA Interaction in SARS-CoV-2 Orf1a

Since the start of the COVID-19 pandemic, understanding the pathology of the SARS-CoV-2 RNA virus and its life cycle has been the priority of many researchers. Currently, new variants of the virus have emerged with various levels of pathogenicity and abundance within the human-host population. Although much of viral pathogenicity is attributed to the viral Spike protein’s binding affinity to human lung cells’ ACE2 receptor, comprehensive knowledge on the distinctive features of viral variants that might affect their life cycle and pathogenicity is yet to be attained. Recent in vivo studies into the RNA structure of the SARS-CoV-2 genome have revealed certain long-range RNA-RNA interactions. Using in silico predictions and a large population of SARS-CoV-2 sequences, we observed variant-specific evolutionary changes for certain long-range RRIs. We also found statistical evidence for the existence of one of the thermodynamic-based RRI predictions, namely Comp1, in the Beta variant sequences. A similar test that disregarded sequence variant information did not, however, lead to significant results. When performing population-based analyses, aggregate tests may fail to identify novel interactions due to variant-specific changes. Variant-specific analyses can result in de novo RRI identification.

Phenotypic mutations contribute to protein diversity and shape protein evolution

Errors in DNA replication generate genetic mutations, while errors in transcription and translation lead to phenotypic mutations. Phenotypic mutations are orders of magnitude more frequent than genetic ones, yet they are less understood. Here, we review the types of phenotypic mutations, their quantifications, and their role in protein evolution and disease. The diversity generated by phenotypic mutation can facilitate adaptive evolution. Indeed, phenotypic mutations, such as ribosomal frameshift and stop codon readthrough, sometimes serve to regulate protein expression and function. Phenotypic mutations have often been linked to fitness decrease and diseases. Thus, understanding the protein heterogeneity and phenotypic diversity caused by phenotypic mutations will advance our understanding of protein evolution and have implications on human health and diseases.

Viruses Broaden the Definition of Life by Genomic Incorporation of Artificial Intelligence and Machine Learning Processes

Viruses have been classified as non-living because they require a cellular host to support their replicative processes. Empirical investigations have significantly advanced our understanding of the many strategies employed by viruses to usurp and divert host regulatory and metabolic processes to drive the synthesis and release of infectious particles. The recent emergence of SARS-CoV-2 has permitted us to evaluate and discuss a potentially novel classification of viruses as living entities. The ability of SARS CoV-2 to engender comprehensive regulatory control of integrative cellular processes is strongly suggestive of an inherently dynamic informational registry that is programmatically encoded by linear ssRNA sequences responding to distinct evolutionary constraints. Responses to positive evolutionary constraints have resulted in a single-stranded RNA viral genome that occupies a threedimensional space defined by conserved base-paring resulting from a complex pattern of both secondary and tertiary structures. Additionally, regulatory control of virus-mediated infectious processes relies on extensive protein-protein interactions that drive conformational matching and shape recognition events to provide a functional link between complementary viral and host nucleic acid and protein domains. We also recognize that the seamless integration of complex replicative processes is highly dependent on the precise temporal matching of complementary nucleotide sequences and their corresponding structural and non-structural viral proteins. Interestingly, the deployment of concerted transcriptional and translational activities within targeted cellular domains may be modeled by artificial intelligence (AI) strategies that are inherently fluid, self-correcting, and adaptive at accommodating temporal changes in host defense mechanisms. An in-depth understanding of multiple self-correcting AIassociated viral processes will most certainly lead to novel therapeutic development platforms, notably the design of efficacious neuropharmacological agents to treat chronic CNS syndromes associated with long-COVID. In summary, it appears that viruses, notably SARS-CoV-2, are very much alive due to acquired genetic advantages that are intimately entrained to existential host processes via evolutionarily constrained AI-associated learning paradigms.

COVIDOA: a novel evolutionary optimization algorithm based on coronavirus disease replication lifecycle

This paper presents a novel bio-inspired optimization algorithm called Coronavirus Optimization Algorithm (COVIDOA). COVIDOA is an evolutionary search strategy that mimics the mechanism of coronavirus when hijacking human cells. COVIDOA is inspired by the frameshifting technique used by the coronavirus for replication. The proposed algorithm is tested using 20 standard benchmark optimization functions with different parameter values. Besides, we utilized five IEEE Congress of Evolutionary Computation (CEC) benchmark test functions (CECC06, 2019 Competition) and five CEC 2011 real-world problems to prove the proposed algorithm's efficiency. The proposed algorithm is compared to eight of the most popular and recent metaheuristic algorithms from the state-of-the-art in terms of best cost, average cost (AVG), corresponding standard deviation (STD), and convergence speed. The results demonstrate that COVIDOA is superior to most existing metaheuristics.

Proteolytic Processing of the Coronavirus Replicase Nonstructural Protein 14 Exonuclease Is Not Required for Virus Replication but Alters RNA Synthesis and Viral Fitness

Coronaviruses (CoVs) initiate replication by translation of the positive-sense RNA genome into the replicase polyproteins connecting 16 nonstructural protein domains (nsp1-16), which are subsequently processed by viral proteases to yield mature nsp. For the betacoronavirus murine hepatitis virus (MHV), total inhibition of translation or proteolytic processing of replicase polyproteins results in rapid cessation of RNA synthesis. The nsp5-3CLpro (Mpro) processes nsps7-16, which assemble into functional replication-transcription complexes (RTCs), including the enzymatic nsp12-RdRp and nsp14-exoribonuclease (ExoN)/N7-methyltransferase. The nsp14-ExoN activity mediates RNA-dependent RNA proofreading, high-fidelity RNA synthesis, and replication. To date, the solved partial RTC structures, biochemistry, and models use or assume completely processed, mature nsp. Here, we demonstrate that in MHV, engineered deletion of the cleavage sites between nsp13-14 and nsp14-15 allowed recovery of replication-competent virus. Compared to wild-type (WT) MHV, the nsp13-14 and nsp14-15 cleavage deletion mutants demonstrated delayed replication kinetics, impaired genome production, altered abundance and patterns of recombination, and impaired competitive fitness. Further, the nsp13-14 and nsp14-15 mutant viruses demonstrated mutation frequencies that were significantly higher than with the WT. The results demonstrate that cleavage of nsp13-14 or nsp14-15 is not required for MHV viability and that functions of the RTC/nsp14-ExoN are impaired when assembled with noncleaved intermediates. These data will inform future genetic, structural, biochemical, and modeling studies of coronavirus RTCs and nsp 13, 14, and 15 and may reveal new approaches for inhibition or attenuation of CoV infection.

IMPORTANCE Coronavirus replication requires proteolytic maturation of the nonstructural replicase proteins to form the replication-transcription complex. Coronavirus replication-transcription complex models assume mature subunits; however, mechanisms of coronavirus maturation and replicase complex formation have yet to be defined. Here, we show that for the coronavirus murine hepatitis virus, cleavage between the nonstructural replicase proteins nsp13-14 and nsp14-15 is not required for replication but does alter RNA synthesis and recombination. These results shed new light on the requirements for coronavirus maturation and replication-transcription complex assembly, and they may reveal novel therapeutic targets and strategies for attenuation.

An intranasal ASO therapeutic targeting SARS-CoV-2

The COVID-19 pandemic is exacting an increasing toll worldwide, with new SARS-CoV-2 variants emerging that exhibit higher infectivity rates and that may partially evade vaccine and antibody immunity. Rapid deployment of non-invasive therapeutic avenues capable of preventing infection by all SARS-CoV-2 variants could complement current vaccination efforts and help turn the tide on the COVID-19 pandemic. Here, we describe a novel therapeutic strategy targeting the SARS-CoV-2 RNA using locked nucleic acid antisense oligonucleotides (LNA ASOs). We identify an LNA ASO binding to the 5′ leader sequence of SARS-CoV-2 that disrupts a highly conserved stem-loop structure with nanomolar efficacy in preventing viral replication in human cells. Daily intranasal administration of this LNA ASO in the COVID-19 mouse model potently suppresses viral replication (>80-fold) in the lungs of infected mice. We find that the LNA ASO is efficacious in countering all SARS-CoV-2 “variants of concern” tested both in vitro and in vivo. Hence, inhaled LNA ASOs targeting SARS-CoV-2 represents a promising therapeutic approach to reduce or prevent transmission and decrease severity of COVID-19 in infected individuals. LNA ASOs are chemically stable and can be flexibly modified to target different viral RNA sequences and could be stockpiled for future coronavirus pandemics.

Despite approved vaccines and anti-virals to prevent and treat SARS-CoV-2 infection, there is a need for further development of efficient antiviral therapeutic strategy. Here, Zhu et al. develop locked nucleic acid antisense oligonucleotides (LNA ASOs) targeting the 5’ leader sequence of SARS-CoV-2 RNA to interfere with replication of wildtype virus and variants of concern. Daily intranasal administration in K18-hACE2 humanized mice suppresses viral infection in lung.

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.

Hyper-swivel head domain motions are required for complete mRNA-tRNA translocation and ribosome resetting

Translocation of messenger RNA (mRNA) and transfer RNA (tRNA) substrates through the ribosome during protein synthesis, an exemplar of directional molecular movement in biology, entails a complex interplay of conformational, compositional, and chemical changes. The molecular determinants of early translocation steps have been investigated rigorously. However, the elements enabling the ribosome to complete translocation and reset for subsequent protein synthesis reactions remain poorly understood. Here, we have combined molecular simulations with single-molecule fluorescence resonance energy transfer imaging to gain insights into the rate-limiting events of the translocation mechanism. We find that diffusive motions of the ribosomal small subunit head domain to hyper-swivelled positions, governed by universally conserved rRNA, can maneuver the mRNA and tRNAs to their fully translocated positions. Subsequent engagement of peptidyl-tRNA and disengagement of deacyl-tRNA from mRNA, within their respective small subunit binding sites, facilitate the ribosome resetting mechanism after translocation has occurred to enable protein synthesis to resume.

Lessons Learned and Yet-to-Be Learned on the Importance of RNA Structure in SARS-CoV-2 Replication

SARS-CoV-2, the etiological agent responsible for the COVID-19 pandemic, is a member of the virus family Coronaviridae, known for relatively extensive (~30-kb) RNA genomes that not only encode for numerous proteins but are also capable of forming elaborate structures. As highlighted in this review, these structures perform critical functions in various steps of the viral life cycle, ultimately impacting pathogenesis and transmissibility. We examine these elements in the context of coronavirus evolutionary history and future directions for curbing the spread of SARS-CoV-2 and other potential human coronaviruses. While we focus on structures supported by a variety of biochemical, biophysical, and/or computational methods, we also touch here on recent evidence for novel structures in both protein-coding and noncoding regions of the genome, including an assessment of the potential role for RNA structure in the controversial finding of SARS-CoV-2 integration in “long COVID” patients. This review aims to serve as a consolidation of previous works on coronavirus and more recent investigation of SARS-CoV-2, emphasizing the need for improved understanding of the role of RNA structure in the evolution and adaptation of these human viruses.

Tracing genetic signatures of bat-to-human coronaviruses and early transmission of North American SARS-CoV-2

Highly pathogenic coronaviruses, including SARS-CoV-2, SARS-CoV and MERS-CoV, are thought to be transmitted from bats to humans, but the viral genetic signatures that contribute to bat-to-human transmission remain largely obscure. In this study, we identified an identical ribosomal frameshift motif among the three bat-human pairs of viruses and strong purifying selection after jumping from bats to humans. This represents genetic signatures of coronaviruses that are related to bat-to-human transmission. To further trace the early human-to-human transmission of SARS-CoV-2 in North America, a geographically stratified genome-wide association study (North American isolates and the remaining isolates) and a retrospective study were conducted. We determined that the single nucleotide polymorphisms (SNPs) 1,059.C > T and 25,563.G > T were significantly associated with approximately half of the North American SARS-CoV-2 isolates that accumulated largely during March 2020. Retrospectively tracing isolates with these two SNPs was used to reconstruct the early, reliable transmission history of North American SARS-CoV-2, and European isolates (February 26, 2020) showed transmission 3 days earlier than North American isolates and 17 days earlier than Asian isolates. Collectively, we identified the genetic signatures of the three pairs of coronaviruses and reconstructed an early transmission history of North American SARS-CoV-2. We envision that these genetic signatures are possibly diagnosable and predic markers for public health surveillance.

Beyond Proteolysis-Targeting Chimeric Molecules: Designing Heterobifunctional Molecules Based on Functional Effectors

In recent years, with the successful development of proteolysis-targeting chimeric molecules (PROTACs), the potential of heterobifunctional molecules to contribute to reenvisioning drug design, especially small-molecule drugs, has been increasingly recognized. Inspired by PROTACs, diverse heterobifunctional molecules have been reported to simultaneously bind two or more molecules and bring them into proximity to interaction, such as ribonuclease-recruiting, autophagy-recruiting, lysosome-recruiting, kinase-recruiting, phosphatase-recruiting, glycosyltransferase-recruiting, and acetyltransferase-recruiting chimeras. On the basis of the heterobifunctional principle, more opportunities for advancing drug design by linking potential effectors to a protein of interest (POI) have emerged. Herein, we introduce heterobifunctional molecules other than PROTACs, summarize the limitations of existing molecules, list the main challenges, and propose perspectives for future research directions, providing insight into alternative design strategies based on substrate-proximity-based targeting.

Abracadabra, One Becomes Two: The Importance of Context in Viral -1 Programmed Ribosomal Frameshifting

The constrained nature of viral genomes has allowed a translational sleight of hand known as −1 Programmed Ribosomal Frameshifting (−1 PRF) to flourish. Numerous studies have sought to tease apart the mechanisms and implications of −1PRF utilizing a few techniques. The dual-luciferase assay and ribosomal profiling have driven the PRF field to make great advances; however, the use of these assays means that the full impact of the genomic and cellular context on −1 PRF is often lost. Here, we discuss how the Minimal Frameshifting Element (MFE) and its constraints can hide contextual effects on −1 PRF. We review how sequence elements proximal to the traditionally defined MFE, such as the coronavirus attenuator sequence, can affect the observed rates of −1 PRF. Further, the MFE-based approach fully obscured −1 PRF in Barley yellow dwarf virus and would render the exploration of −1 PRF difficult in Porcine reproductive and respiratory syndrome virus, Encephalomyocarditis virus, Theiler’s murine encephalomyelitis virus, and Sindbis virus. Finally, we examine how the cellular context of tRNA abundance, miRNAs, and immune response elements can affect −1 PRF. The use of MFE was instrumental in establishing the basic foundations of PRF; however, it has become clear that the contextual impact on −1 PRF is no longer the exception so much as it is the rule and argues for new approaches to study −1PRF that embrace context. We therefore urge our field to expand the strategies and methods used to explore −1 PRF.

Applicability of the nearest-neighbour model for pseudoknot RNAs

The validity of the nearest-neighbour (NN) model was verified in an RNA pseudoknot (PK) structure. The thermodynamic parameters of the second hairpin stem (S2) region, which separates the PK from a hairpin structure, were monitored using CD and UV melting. Different PKs with identical NN base pairs in the S2 region exhibited similar thermodynamic parameters, highlighting the validity of the NN model in this RNA tertiary structure motif.

The Evolutionary Dance between Innate Host Antiviral Pathways and SARS-CoV-2

Compared to what we knew at the start of the SARS-CoV-2 global pandemic, our understanding of the interplay between the interferon signaling pathway and SARS-CoV-2 infection has dramatically increased. Innate antiviral strategies range from the direct inhibition of viral components to reprograming the host’s own metabolic pathways to block viral infection. SARS-CoV-2 has also evolved to exploit diverse tactics to overcome immune barriers and successfully infect host cells. Herein, we review the current knowledge of the innate immune signaling pathways triggered by SARS-CoV-2 with a focus on the type I interferon response, as well as the mechanisms by which SARS-CoV-2 impairs those defenses.

Translational Control of COVID-19 and Its Therapeutic Implication

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of COVID-19, which has broken out worldwide for more than two years. However, due to limited treatment, new cases of infection are still rising. Therefore, there is an urgent need to understand the basic molecular biology of SARS-CoV-2 to control this virus. SARS-CoV-2 replication and spread depend on the recruitment of host ribosomes to translate viral messenger RNA (mRNA). To ensure the translation of their own mRNAs, the SARS-CoV-2 has developed multiple strategies to globally inhibit the translation of host mRNAs and block the cellular innate immune response. This review provides a comprehensive picture of recent advancements in our understanding of the molecular basis and complexity of SARS-CoV-2 protein translation. Specifically, we summarize how this viral infection inhibits host mRNA translation to better utilize translation elements for translation of its own mRNA. Finally, we discuss the potential of translational components as targets for therapeutic interventions.

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.

Specific length and structure rather than high thermodynamic stability enable regulatory mRNA stem-loops to pause translation

Translating ribosomes unwind mRNA secondary structures by three basepairs each elongation cycle. Despite the ribosome helicase, certain mRNA stem-loops stimulate programmed ribosomal frameshift by inhibiting translation elongation. Here, using mutagenesis, biochemical and single-molecule experiments, we examine whether high stability of three basepairs, which are unwound by the translating ribosome, is critical for inducing ribosome pauses. We find that encountering frameshift-inducing mRNA stem-loops from the E. coli dnaX mRNA and the gag-pol transcript of Human Immunodeficiency Virus (HIV) hinders A-site tRNA binding and slows down ribosome translocation by 15-20 folds. By contrast, unwinding of first three basepairs adjacent to the mRNA entry channel slows down the translating ribosome by only 2-3 folds. Rather than high thermodynamic stability, specific length and structure enable regulatory mRNA stem-loops to stall translation by forming inhibitory interactions with the ribosome. Our data provide the basis for rationalizing transcriptome-wide studies of translation and searching for novel regulatory mRNA stem-loops.

Thinking Outside the Frame: Impacting Genomes Capacity by Programmed Ribosomal Frameshifting

Translation facilitates the transfer of the genetic information stored in the genome via messenger RNAs to a functional protein and is therefore one of the most fundamental cellular processes. Programmed ribosomal frameshifting is a ubiquitous alternative translation event that is extensively used by viruses to regulate gene expression from overlapping open reading frames in a controlled manner. Recent technical advances in the translation field enabled the identification of precise mechanisms as to how and when ribosomes change the reading frame on mRNAs containing cis-acting signals. Several studies began also to illustrate that trans-acting RNA modulators can adjust the timing and efficiency of frameshifting illuminating that frameshifting can be a dynamically regulated process in cells. Here, we intend to summarize these new findings and emphasize how it fits in our current understanding of PRF mechanisms as previously described.

Targeting SARS-CoV-2 Proteases for COVID-19 Antiviral Development

The emergence of severe acute respiratory syndrome (SARS-CoV-2) in 2019 marked the third occurrence of a highly pathogenic coronavirus in the human population since 2003. As the death toll surpasses 5 million globally and economic losses continue, designing drugs that could curtail infection and disease progression is critical. In the US, three highly effective Food and Drug Administration (FDA)-authorized vaccines are currently available, and Remdesivir is approved for the treatment of hospitalized patients. However, moderate vaccination rates and the sustained evolution of new viral variants necessitate the ongoing search for new antivirals. Several viral proteins have been prioritized as SARS-CoV-2 antiviral drug targets, among them the papain-like protease (PLpro) and the main protease (Mpro). Inhibition of these proteases would target viral replication, viral maturation, and suppression of host innate immune responses. Knowledge of inhibitors and assays for viruses were quickly adopted for SARS-CoV-2 protease research. Potential candidates have been identified to show inhibitory effects against PLpro and Mpro, both in biochemical assays and viral replication in cells. These results encourage further optimizations to improve prophylactic and therapeutic efficacy. In this review, we examine the latest developments of potential small-molecule inhibitors and peptide inhibitors for PLpro and Mpro, and how structural biology greatly facilitates this process.

Crystal structure of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) frameshifting pseudoknot

SARS-CoV-2 produces two long viral protein precursors from one open reading frame using a highly conserved RNA pseudoknot that enhances programmed -1 ribosomal frameshifting. The 1.3 Å-resolution X-ray structure of the pseudoknot reveals three coaxially stacked helices buttressed by idiosyncratic base triples from loop residues. This structure represents a frameshift-stimulating state that must be deformed by the ribosome and exhibits base-triple-adjacent pockets that could be targeted by future small-molecule therapeutics.

Identifying Inhibitors of −1 Programmed Ribosomal Frameshifting in a Broad Spectrum of Coronaviruses

Recurrent outbreaks of novel zoonotic coronavirus (CoV) diseases in recent years have highlighted the importance of developing therapeutics with broad-spectrum activity against CoVs. Because all CoVs use −1 programmed ribosomal frameshifting (−1 PRF) to control expression of key viral proteins, the frameshift signal in viral mRNA that stimulates −1 PRF provides a promising potential target for such therapeutics. To test the viability of this strategy, we explored whether small-molecule inhibitors of −1 PRF in SARS-CoV-2 also inhibited −1 PRF in a range of bat CoVs—the most likely source of future zoonoses. Six inhibitors identified in new and previous screens against SARS-CoV-2 were evaluated against the frameshift signals from a panel of representative bat CoVs as well as MERS-CoV. Some drugs had strong activity against subsets of these CoV-derived frameshift signals, while having limited to no effect on −1 PRF caused by frameshift signals from other viruses used as negative controls. Notably, the serine protease inhibitor nafamostat suppressed −1 PRF significantly for multiple CoV-derived frameshift signals. These results suggest it is possible to find small-molecule ligands that inhibit −1 PRF specifically in a broad spectrum of CoVs, establishing frameshift signals as a viable target for developing pan-coronaviral therapeutics.

Emerging roles of RNA-RNA interactions in transcriptional regulation

Pervasive transcription of the human genome generates a massive amount of noncoding RNAs (ncRNAs) that lack protein-coding potential but play crucial roles in development, differentiation, and tumorigenesis. To achieve these biological functions, ncRNAs must first fold into intricate structures via intramolecular RNA-RNA interactions (RRIs) and then interact with different RNA substrates via intermolecular RRIs. RRIs are usually facilitated, stabilized, or mediated by RNA-binding proteins. With this guiding principle, several protein-based high-throughput methods have been developed for unbiased mapping of defined or all RNA-binding protein-mediated RRIs in various species and cell lines. In addition, some chemical-based approaches are also powerful to detect RRIs globally based on the fact that RNA duplex can be cross-linked by psoralen or its derivative 4'-aminomethyltrioxsalen. These efforts have significantly expanded our understanding of RRIs in determining the specificity and variability of gene regulation. Here, we review the current knowledge of the regulatory roles of RRI, focusing on their emerging roles in transcriptional regulation and nuclear body formation. This article is categorized under: RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry.

Computational anti-COVID-19 drug design: progress and challenges

Vaccines have made gratifying progress in preventing the 2019 coronavirus disease (COVID-19) pandemic. However, the emergence of variants, especially the latest delta variant, has brought considerable challenges to human health. Hence, the development of robust therapeutic approaches, such as anti-COVID-19 drug design, could aid in managing the pandemic more efficiently. Some drug design strategies have been successfully applied during the COVID-19 pandemic to create and validate related lead drugs. The computational drug design methods used for COVID-19 can be roughly divided into (i) structure-based approaches and (ii) artificial intelligence (AI)-based approaches. Structure-based approaches investigate different molecular fragments and functional groups through lead drugs and apply relevant tools to produce antiviral drugs. AI-based approaches usually use end-to-end learning to explore a larger biochemical space to design antiviral drugs. This review provides an overview of the two design strategies of anti-COVID-19 drugs, the advantages and disadvantages of these strategies and discussions of future developments.

Recent advances in small-angle scattering and its expanding impact in structural biology

Applications of small-angle scattering (SAS) in structural biology have benefited from continuing developments in instrumentation, tools for data analysis, modeling capabilities, standards for data and model presentation, and data archiving. The interplay of these capabilities has enabled SAS to contribute to advances in structural biology as the field pushes the boundaries in studies of biomolecular complexes and assemblies as large as whole cells, membrane proteins in lipid environments, and dynamic systems on time scales ranging from femtoseconds to hours. This review covers some of the important advances in biomolecular SAS capabilities for structural biology focused on over the last 5 years and presents highlights of recent applications that demonstrate how the technique is exploring new territories.

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

Conserved SARS-CoV-2 RNA regions of critical biological functions define excellent targets for anti-viral therapeutics against Covid-19 variants. One such region is the frameshifting element (FSE), responsible for correct translation of viral polyproteins. Here, we analyze molecular-dynamics motions of three FSE conformations, discovered by graph-theory analysis, and associated mutants designed by graph-based inverse folding: two distinct 3-stem H-type pseudoknots and a 3-way junction. We find that the prevalent H-type pseudoknot in literature adopts ring-like conformations, which in combination with 5' end threading could promote ribosomal pausing. An inherent shape switch from "L" to linear that may help trigger the frameshifting is suppressed in our designed mutant. The alternative conformation trajectories suggest a stable intermediate structure with mixed stem interactions of all three conformations, pointing to a possible transition pathway during ribosomal translation. These observations provide new insights into anti-viral strategies and frameshifting mechanisms.

LinearTurboFold: Linear-time global prediction of conserved structures for RNA homologs with applications to SARS-CoV-2

The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length and are thus infeasible for coronaviruses, which possess the longest genomes (∼30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single-sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurboFold's purely in silico prediction not only is close to experimentally guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5' and 3' untranslated regions (UTRs) (∼29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies undiscovered conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, small interfering RNAs (siRNAs), CRISPR-Cas13 guide RNAs, and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies and will be a useful tool in fighting the current and future pandemics.

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

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

SARS-COV-2, infection, transmission, transcription, translation, proteins, and treatment: A review

In this review, we describe the key molecular entities involved in the process of infection by SARS-CoV-2, while also detailing how those key entities influence the spread of the disease. We further introduce the molecular mechanisms of preventive and treatment strategies including drugs, antibodies, and vaccines.

Stepwise Evolution and Exceptional Conservation of ORF1a/b Overlap in Coronaviruses

The programmed frameshift element (PFE) rerouting translation from ORF1a to ORF1b is essential for the propagation of coronaviruses. The combination of genomic features that make up PFE-the overlap between the two reading frames, a slippery sequence, as well as an ensemble of complex secondary structure elements-places severe constraints on this region as most possible nucleotide substitution may disrupt one or more of these elements. The vast amount of SARS-CoV-2 sequencing data generated within the past year provides an opportunity to assess the evolutionary dynamics of PFE in great detail. Here, we performed a comparative analysis of all available coronaviral genomic data available to date. We show that the overlap between ORF1a and ORF1b evolved as a set of discrete 7, 16, 22, 25, and 31 nucleotide stretches with a well-defined phylogenetic specificity. We further examined sequencing data from over 1,500,000 complete genomes and 55,000 raw read data sets to demonstrate exceptional conservation and detect signatures of selection within the PFE region.

Semi-Supervised Pipeline for Autonomous Annotation of SARS-CoV-2 Genomes

SARS-CoV-2 genomic sequencing efforts have scaled dramatically to address the current global pandemic and aid public health. However, autonomous genome annotation of SARS-CoV-2 genes, proteins, and domains is not readily accomplished by existing methods and results in missing or incorrect sequences. To overcome this limitation, we developed a novel semi-supervised pipeline for automated gene, protein, and functional domain annotation of SARS-CoV-2 genomes that differentiates itself by not relying on the use of a single reference genome and by overcoming atypical genomic traits that challenge traditional bioinformatic methods. We analyzed an initial corpus of 66,000 SARS-CoV-2 genome sequences collected from labs across the world using our method and identified the comprehensive set of known proteins with 98.5% set membership accuracy and 99.1% accuracy in length prediction, compared to proteome references, including Replicase polyprotein 1ab (with its transcriptional slippage site). Compared to other published tools, such as Prokka (base) and VAPiD, we yielded a 6.4- and 1.8-fold increase in protein annotations. Our method generated 13,000,000 gene, protein, and domain sequences-some conserved across time and geography and others representing emerging variants. We observed 3362 non-redundant sequences per protein on average within this corpus and described key D614G and N501Y variants spatiotemporally in the initial genome corpus. For spike glycoprotein domains, we achieved greater than 97.9% sequence identity to references and characterized receptor binding domain variants. We further demonstrated the robustness and extensibility of our method on an additional 4000 variant diverse genomes containing all named variants of concern and interest as of August 2021. In this cohort, we successfully identified all keystone spike glycoprotein mutations in our predicted protein sequences with greater than 99% accuracy as well as demonstrating high accuracy of the protein and domain annotations. This work comprehensively presents the molecular targets to refine biomedical interventions for SARS-CoV-2 with a scalable, high-accuracy method to analyze newly sequenced infections as they arise.

Discovery of highly reactive self-splicing group II introns within the mitochondrial genomes of human pathogenic fungi

Fungal pathogens represent an expanding global health threat for which treatment options are limited. Self-splicing group II introns have emerged as promising drug targets, but their development has been limited by a lack of information on their distribution and architecture in pathogenic fungi. To meet this challenge, we developed a bioinformatic workflow for scanning sequence data to identify unique RNA structural signatures within group II introns. Using this approach, we discovered a set of ubiquitous introns within thermally dimorphic fungi (genera of Blastomyces, Coccidioides and Histoplasma). These introns are the most biochemically reactive group II introns ever reported, and they self-splice rapidly under near-physiological conditions without protein cofactors. Moreover, we demonstrated the small molecule targetability of these introns by showing that they can be inhibited by the FDA-approved drug mitoxantrone in vitro. Taken together, our results highlight the utility of structure-based informatic searches for identifying riboregulatory elements in pathogens, revealing a striking diversity of reactive self-splicing introns with great promise as antifungal drug targets.

Amilorides inhibit SARS-CoV-2 replication in vitro by targeting RNA structures

The SARS-CoV-2 pandemic, and the likelihood of future coronavirus pandemics, emphasized the urgent need for development of novel antivirals. Small-molecule chemical probes offer both to reveal aspects of virus replication and to serve as leads for antiviral therapeutic development. Here, we report on the identification of amiloride-based small molecules that potently inhibit OC43 and SARS-CoV-2 replication through targeting of conserved structured elements within the viral 5′-end. Nuclear magnetic resonance–based structural studies revealed specific amiloride interactions with stem loops containing bulge like structures and were predicted to be strongly bound by the lead amilorides in retrospective docking studies. Amilorides represent the first antiviral small molecules that target RNA structures within the 5′ untranslated regions and proximal region of the CoV genomes. These molecules will serve as chemical probes to further understand CoV RNA biology and can pave the way for the development of specific CoV RNA–targeted antivirals.

LinearTurboFold: Linear-Time Global Prediction of Conserved Structures for RNA Homologs with Applications to SARS-CoV-2

The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in SARS-CoV-2 genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length, and are thus infeasible for coronaviruses, which possess the longest genomes (∼30,000 nt ) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurbo-Fold's purely in silico prediction not only is close to experimentally-guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5' and 3' UTRs (∼29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies novel conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, siRNAs, CRISPR-Cas13 guide RNAs and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies, and will be a useful tool in fighting the current and future pandemics.

SIGNIFICANCE STATEMENT

Conserved RNA structures are critical for designing diagnostic and therapeutic tools for many diseases including COVID-19. However, existing algorithms are much too slow to model the global structures of full-length RNA viral genomes. We present LinearTurboFold, a linear-time algorithm that is orders of magnitude faster, making it the first method to simultaneously fold and align whole genomes of SARS-CoV-2 variants, the longest known RNA virus (∼30 kilobases). Our work enables unprecedented global structural analysis and captures long-range interactions that are out of reach for existing algorithms but crucial for RNA functions. LinearTurboFold is a general technique for full-length genome studies and can help fight the current and future pandemics.

Prediction of the Effects of Synonymous Variants on SARS-CoV-2 Genome

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 studies had been done to identify and study nonsynonymous mutations, which change amino acid residues of SARS-CoV-2 proteins. On the other hand, there is little study on the effects of SARS-CoV-2 synonymous mutations. Although these mutations do not alter amino acids, some studies suggest that they may affect viral fitness. This study aims to predict the effect of synonymous mutations on the SARS-CoV-2 genome.   Methods: A total of 30,229 SARS-CoV-2 genomic sequences were retrieved from Global Initiative on Sharing all Influenza Data (GISAID) database and aligned using MAFFT. Then, the mutations and their respective frequency were identified. A prediction of RNA secondary structures and their base pair probabilities was performed to study the effect of synonymous mutations on RNA structure and stability. 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, followed by C313U and C9286U mutation in nsp1 and nsp4 of ORF1a, respectively.   Conclusion: Among the synonymous mutations identified, C913U mutation in ORF1a and C26735U in membrane (M) protein may affect RNA secondary structure, reducing the stability of RNA folding and possibly resulting in a higher translation rate. However, lab experiments are required to validate the results obtained from prediction analysis.

Prediction of RNA secondary structure including pseudoknots for long sequences

RNA structural elements called pseudoknots are involved in various biological phenomena including ribosomal frameshifts. Because it is infeasible to construct an efficiently computable secondary structure model including pseudoknots, secondary structure prediction methods considering pseudoknots are not yet widely available. We developed IPknot, which uses heuristics to speed up computations, but it has remained difficult to apply it to long sequences, such as messenger RNA and viral RNA, because it requires cubic computational time with respect to sequence length and has threshold parameters that need to be manually adjusted. Here, we propose an improvement of IPknot that enables calculation in linear time by employing the LinearPartition model and automatically selects the optimal threshold parameters based on the pseudo-expected accuracy. In addition, IPknot showed favorable prediction accuracy across a wide range of conditions in our exhaustive benchmarking, not only for single sequences but also for multiple alignments.

Targeting SARS-CoV-2 Variants with Nucleic Acid Therapeutic Nanoparticle Conjugates

The emergence of SARS-CoV-2 variants is cause for concern, because these may become resistant to current vaccines and antiviral drugs in development. Current drugs target viral proteins, resulting in a critical need for RNA-targeted nanomedicines. To address this, a comparative analysis of SARS-CoV-2 variants was performed. Several highly conserved sites were identified, of which the most noteworthy is a partial homopurine palindrome site with >99% conservation within the coding region. This sequence was compared among recently emerged, highly infectious SARS-CoV-2 variants. Conservation of the site was maintained among these emerging variants, further contributing to its potential as a regulatory target site for SARS-CoV-2. RNAfold was used to predict the structures of the highly conserved sites, with some resulting structures being common among coronaviridae. An RNA-level regulatory map of the conserved regions of SARS-CoV-2 was produced based on the predicted structures, with each representing potential target sites for antisense oligonucleotides, triplex-forming oligomers, and aptamers. Additionally, homopurine/homopyrimidine sequences within the viral genome were identified. These sequences also demonstrate appropriate target sites for antisense oligonucleotides and triplex-forming oligonucleotides. An experimental strategy to investigate these is summarized along with potential nanoparticle types for delivery, and the advantages and disadvantages of each are discussed.