Search Results (41)

G-quadruplexes (G4s) are emerging as potential antiviral targets. SARS-CoV-2 genomic RNA contains 42 G-rich regions harboring putative G-quadruplex-forming sequences (PQSs). Here, we performed a systematic genomic and structural analysis of SARS-CoV-2 PQSs. It was proposed that non-G-tetrads or different triads may stabilize most G4s in this RNA. Many G4s may include the most stable U·A-U triad. Several G-quadruplexes may be significantly stabilized by 3′ U-tetrad. Large-scale mutational analysis of RNA structural elements containing PQSs showed that most PQSs are highly conserved, while persistent G4-destroying mutations were observed only for one PQS and were transient for two others. Based on G4 position and structural context, we propose that: (i) G4 370 in nsp1 may contribute to cap-independent translation initiation; (ii) certain putative G4s in different genes may assist in co-translational folding of viral proteins; (iii) G4 13385, located upstream of the frameshift stimulation element, may promote formation of a pseudoknot competent for −1 frameshifting. For putative G4s at positions 3467, 13385 and 28903, we analyzed binding to 13 compounds by molecular docking and selected four candidates for molecular dynamics simulations. The ligand EKM emerged as a promising antiviral candidate due to its specific binding to G4 3467. Full article

Human immunodeficiency virus (HIV) continues to be a threat to public health. An emerging technique with promise in the context of fighting HIV type 1 (HIV-1) focuses on targeting ribosomal frameshifting. A crucial –1 programmed ribosomal frameshift (PRF) has been observed in several pathogenic viruses, including HIV-1. Altered folds of the HIV-1 RNA frameshift element (FSE) have been shown to alter frameshifting efficiency. Here, we use RNA-As-Graphs (RAG), a graph-theory based framework for representing and analyzing RNA secondary structures, to perform conformational analysis in motif space to propose how sequence length may influence folding patterns. This combined analysis, along with all-atom modeling and experimental testing of our designed mutants, has already proven valuable for the SARS-CoV-2 FSE. As a first step to launching the same computational/experimental approach for HIV-1, we compare prior experiments and perform SHAPE-guided 2D-fold predictions for the HIV-1 FSE embedded in increasing sequence contexts and predict structure-altering mutations. We find a highly stable upper stem and highly flexible lower stem for the core FSE, with a three-way junction connecting to other motifs at increasing lengths. In particular, we find little support for a pseudoknot or triplex interaction in the core FSE, although pseudoknots can form separately as a connective motif at longer sequences. We also identify sensitive residues in the upper stem and central loop that, when minimally mutated, alter the core stem loop folding. These insights into the FSE fold and structure-altering mutations can be further pursued by all-atom simulations and experimental testing to advance the mechanistic understanding and therapeutic strategies for HIV-1. Full article

Understanding the structural intricacies of RNA molecules is essential for deciphering numerous biological processes. Traditionally, scientists have relied on experimental methods to gain insights and draw conclusions. However, the recent advent of advanced computational techniques has significantly accelerated and refined the accuracy of research results in several areas. A particularly challenging aspect of RNA analysis is the prediction of its secondary structure, which is crucial for elucidating its functional role in biological systems. This paper deals with the prediction of pseudoknots in RNA, focusing on two types of pseudoknots: K-type and M-type pseudoknots. Pseudoknots are complex RNA formations in which nucleotides in a loop form base pairs with nucleotides outside the loop, and thus contribute to essential biological functions. Accurate prediction of these structures is crucial for understanding RNA dynamics and interactions. Building on our previous work, in which we developed a framework for the recognition of H- and L-type pseudoknots, an extended grammar-based framework tailored to the prediction of K- and M-type pseudoknots is proposed. This approach uses syntactic pattern recognition techniques and provides a systematic method to identify and characterize these complex RNA structures. Our framework uses context-free grammars (CFGs) to model RNA sequences and predict the occurrence of pseudoknots. By formulating specific grammatical rules for type K- and M-type pseudoknots, we enable efficient parsing of RNA sequences to recognize potential pseudoknot configurations. This method ensures an exhaustive exploration of possible pseudoknot structures within a reasonable time frame. In addition, the proposed method incorporates essential concepts of biology, such as base pairing optimization and free energy reduction, to improve the accuracy of pseudoknot prediction. These principles are crucial to ensure that the predicted structures are biologically plausible. By embedding these principles into our grammar-based framework, we aim to predict RNA conformations that are both theoretically sound and biologically relevant. Full article

Sequence analysis of the Zaire ebolavirus (EBOV) polymerase (L gene) mRNA, using online tools, identified a highly ranked −1 programmed ribosomal frameshift (FS) signal including an ideal slippery sequence heptamer (UUUAAAA), with an overlapping coding region featuring two tandem UGA codons, immediately followed by an RNA region that is the inverse complement (antisense) to a region of the mRNA of the selenoprotein iodothyronine deiodinase II (DIO2). This antisense interaction was confirmed in vitro via electrophoretic gel shift assay, using cDNAs at the EBOV and DIO2 segments. The formation of a duplex between the two mRNAs could trigger the ribosomal frameshift, by mimicking the enhancing role of a pseudoknot structure, while providing access to the selenocysteine insertion sequence (SECIS) element contained in the DIO2 mRNA. This process would allow the −1 frame UGA codons to be recoded as selenocysteine, forming part of a C-terminal module in a low abundance truncated isoform of the viral polymerase, potentially functioning in a redox role. Remarkably, 90 bases downstream of the −1 FS site, an active +1 FS site can be demonstrated, which, via a return to the zero frame, would enable the attachment of the entire C-terminal of the polymerase protein. Using a construct with upstream and downstream reporter genes, spanning a wildtype or mutated viral insert, we show significant +1 ribosomal frameshifting at this site. Acting singly or together, frameshifting at these sites (both of which are highly conserved in EBOV strains) could enable the expression of several modified isoforms of the polymerase. The 3D modeling of the predicted EBOV polymerase FS variants using the AI tool, AlphaFold, reveals a peroxiredoxin-like active site with arginine and threonine residues adjacent to a putative UGA-encoded selenocysteine, located on the back of the polymerase “hand”. This module could serve to protect the viral RNA from peroxidative damage. Full article

In the SARS-CoV-2 lineage, RNA elements essential for its viral life cycle, including genome replication and gene expression, have been identified. Still, the precise structures and functions of these RNA regions in coronaviruses remain poorly understood. This lack of knowledge points out the need for further research to better understand these crucial aspects of viral biology and, in time, prepare for future outbreaks. In this research, the in silico analysis of the cis RNA structures that act in the alpha-, beta-, gamma-, and deltacoronavirus genera has provided a detailed view of the presence and adaptation of the structures of these elements in coronaviruses. The results emphasize the importance of these cis elements in viral biology and their variability between different viral variants. Some coronavirus variants in some groups, depending on the cis element (stem-loop1 and -2; pseudoknot stem-loop1 and -2, and s2m), exhibited functional adaptation. Additionally, the conformation flexibility of the s2m element in the SARS variants was determined, suggesting a coevolution of this element in this viral group. The variability in secondary structures suggests genomic adaptations that may be related to replication processes, genetic regulation, as well as the specific pathogenicity of each variant. The results suggest that RNA structures in coronaviruses can adapt and evolve toward different viral variants, which has important implications for viral adaptation, pathogenicity, and future therapeutic strategies. Full article

Accurately predicting the pairing order of bases in RNA molecules is essential for anticipating RNA secondary structures. Consequently, this task holds significant importance in unveiling previously unknown biological processes. The urgent need to comprehend RNA structures has been accentuated by the unprecedented impact of the widespread COVID-19 pandemic. This paper presents a framework, Knotify_V2.0, which makes use of syntactic pattern recognition techniques in order to predict RNA structures, with a specific emphasis on tackling the demanding task of predicting H-type pseudoknots that encompass bulges and hairpins. By leveraging the expressive capabilities of a Context-Free Grammar (CFG), the suggested framework integrates the inherent benefits of CFG and makes use of minimum free energy and maximum base pairing criteria. This integration enables the effective management of this inherently ambiguous task. The main contribution of Knotify_V2.0 compared to earlier versions lies in its capacity to identify additional motifs like bulges and hairpins within the internal loops of the pseudoknot. Notably, the proposed methodology, Knotify_V2.0, demonstrates superior accuracy in predicting core stems compared to state-of-the-art frameworks. Knotify_V2.0 exhibited exceptional performance by accurately identifying both core base pairing that form the ground truth pseudoknot in 70% of the examined sequences. Furthermore, Knotify_V2.0 narrowed the performance gap with Knotty, which had demonstrated better performance than Knotify and even surpassed it in Recall and F1-score metrics. Knotify_V2.0 achieved a higher count of true positives (tp) and a significantly lower count of false negatives (fn) compared to Knotify, highlighting improvements in Prediction and Recall metrics, respectively. Consequently, Knotify_V2.0 achieved a higher F1-score than any other platform. The source code and comprehensive implementation details of Knotify_V2.0 are publicly available on GitHub. Full article

The dicistrovirus intergenic (IGR) IRES uses the most streamlined translation initiation mechanism: the IRES recruits ribosomes directly without using protein factors and initiates translation from a non-AUG codon. Several subtypes of dicistroviruses IRES have been identified; typically, the IRESs adopt two -to three overlapping pseudoknots with key stem-loop and unpaired regions that interact with specific domains of the ribosomal 40S and 60S subunits to direct translation. We previously predicted an atypical IGR IRES structure and a potential -1 programmed frameshift (-1 FS) signal within the genome of the whitefly Bemisia-associated dicistrovirus 2 (BaDV-2). Here, using bicistronic reporters, we demonstrate that the predicted BaDV-2 -1 FS signal can drive -1 frameshifting in vitro via a slippery sequence and a downstream stem-loop structure that would direct the translation of the viral RNA-dependent RNA polymerase. Moreover, the predicted BaDV-2 IGR can support IRES translation in vitro but does so through a mechanism that is not typical of known factorless dicistrovirus IGR IRES mechanisms. Using deletion and mutational analyses, the BaDV-2 IGR IRES is mapped within a 140-nucleotide element and initiates translation from an AUG codon. Moreover, the IRES does not bind directly to purified ribosomes and is sensitive to eIF2 and eIF4A inhibitors NSC1198983 and hippuristanol, respectively, indicating an IRES-mediated factor-dependent mechanism. Biophysical characterization suggests the BaDV-2 IGR IRES contains several stem-loops; however, mutational analysis suggests a model whereby the IRES is unstructured or adopts distinct conformations for translation initiation. In summary, we have provided evidence of the first -1 FS frameshifting signal and a novel factor-dependent IRES mechanism in this dicistrovirus family, thus highlighting the diversity of viral RNA-structure strategies to direct viral protein synthesis. Full article

Novel segmented tick-borne RNA viruses belonging to the group of Jingmenviruses (JMVs) are widespread across Africa, Asia, Europe, and America. In this work, we obtained whole-genome sequences of two Kindia tick virus (KITV) isolates and performed modeling and the functional annotation of the secondary structure of 5′ and 3′ UTRs from JMV and KITV viruses. UTRs of various KITV segments are characterized by the following points: (1) the polyadenylated 3′ UTR; (2) 5′ DAR and 3′ DAR motifs; (3) a highly conserved 5′-CACAG-3′ pentanucleotide; (4) a binding site of the La protein; (5) multiple UAG sites providing interactions with the MSI1 protein; (6) three homologous sequences in the 5′ UTR and 3′ UTR of segment 2; (7) the segment 2 3′ UTR of a KITV/2017/1 isolate, which comprises two consecutive 40 nucleotide repeats forming a Y-3 structure; (8) a 35-nucleotide deletion in the second repeat of the segment 2 3′ UTR of KITV/2018/1 and KITV/2018/2 isolates, leading to a modification of the Y-3 structure; (9) two pseudoknots in the segment 2 3′ UTR; (10) the 5′ UTR and 3′ UTR being represented by patterns of conserved motifs; (11) the 5′-CAAGUG-3′ sequence occurring in early UTR hairpins. Thus, we identified regulatory elements in the UTRs of KITV, which are characteristic of orthoflaviviruses. This suggests that they hold functional significance for the replication of JMVs and the evolutionary similarity between orthoflaviviruses and segmented flavi-like viruses. Full article

Specific sequences within RNA encoded by human genes essential for survival possess the ability to activate the RNA-dependent stress kinase PKR, resulting in phosphorylation of its substrate, eukaryotic translation initiation factor-2α (eIF2α), either to curb their mRNA translation or to enhance mRNA splicing. Thus, interferon-γ (IFNG) mRNA activates PKR through a 5′-terminal 203-nucleotide pseudoknot structure, thereby strongly downregulating its own translation and preventing a harmful hyper-inflammatory response. Tumor necrosis factor-α (TNF) pre-mRNA encodes within the 3′-untranslated region (3′-UTR) a 104-nucleotide RNA pseudoknot that activates PKR to enhance its splicing by an order of magnitude while leaving mRNA translation intact, thereby promoting effective TNF protein expression. Adult and fetal globin genes encode pre-mRNA structures that strongly activate PKR, leading to eIF2α phosphorylation that greatly enhances spliceosome assembly and splicing, yet also structures that silence PKR activation upon splicing to allow for unabated globin mRNA translation essential for life. Regulatory circuits resulting in each case from PKR activation were reviewed previously. Here, we analyze mutations within these genes created to delineate the RNA structures that activate PKR and to deconvolute their folding. Given the critical role of intragenic RNA activators of PKR in gene regulation, such mutations reveal novel potential RNA targets for human disease. Full article

Ribosomal frameshifting (RFS) at the slippery site of SARS-CoV-2 RNA is essential for the biosynthesis of the viral replication machinery. It requires the formation of a pseudoknot (PK) structure near the slippery site and can be inhibited by PK-disrupting oligonucleotide-based antivirals. We obtained and compared three types of such antiviral candidates, namely locked nucleic acids (LNA), LNA–DNA gapmers, and G-clamp-containing phosphorothioates (CPSs) complementary to PK stems. Using optical and electrophoretic methods, we showed that stem 2-targeting oligonucleotide analogs induced PK unfolding at nanomolar concentrations, and this effect was particularly pronounced in the case of LNA. For the leading PK-unfolding LNA and CPS oligonucleotide analogs, we also demonstrated dose-dependent RSF inhibition in dual luciferase assays (DLAs). Finally, we showed that the leading oligonucleotide analogs reduced SARS-CoV-2 replication at subtoxic concentrations in the nanomolar range in two human cell lines. Our findings highlight the promise of PK targeting, illustrate the advantages and limitations of various types of DNA modifications and may promote the future development of oligonucleotide-based antivirals. Full article

This paper presents ConF, a novel deep learning model designed for accurate and efficient prediction of noncoding RNA families. NcRNAs are essential functional RNA molecules involved in various cellular processes, including replication, transcription, and gene expression. Identifying ncRNA families is crucial for comprehensive RNA research, as ncRNAs within the same family often exhibit similar functionalities. Traditional experimental methods for identifying ncRNA families are time-consuming and labor-intensive. Computational approaches relying on annotated secondary structure data face limitations in handling complex structures like pseudoknots and have restricted applicability, resulting in suboptimal prediction performance. To overcome these challenges, ConF integrates mainstream techniques such as residual networks with dilated convolutions and cross multi-head attention mechanisms. By employing a combination of dual-layer convolutional networks and BiLSTM, ConF effectively captures intricate features embedded within RNA sequences. This feature extraction process leads to significantly improved prediction accuracy compared to existing methods. Experimental evaluations conducted using a single, publicly available dataset and applying ten-fold cross-validation demonstrate the superiority of ConF in terms of accuracy, sensitivity, and other performance metrics. Overall, ConF represents a promising solution for accurate and efficient ncRNA family prediction, addressing the limitations of traditional experimental and computational methods. Full article

The transient activation of the cellular stress kinase, protein kinase RNA-activated (PKR), by double-helical RNA, especially by viral double-stranded RNA generated during replication, results in the inhibition of translation via the phosphorylation of eukaryotic initiation factor 2 α-chain (eIF2α). Exceptionally, short intragenic elements within primary transcripts of the human tumor necrosis factor (TNF-α) and globin genes, genes essential for survival, can form RNA structures that strongly activate PKR and thereby render the splicing of their mRNAs highly efficient. These intragenic RNA activators of PKR promote early spliceosome assembly and splicing by inducing phosphorylation of nuclear eIF2α, without impairing the translation of the mature spliced mRNA. Unexpectedly, excision of the large human immunodeficiency virus (HIV) rev/tat intron was shown to require activation of PKR by the viral RNA and eIF2α phosphorylation. The splicing of rev/tat mRNA is abrogated by viral antagonists of PKR and by trans-dominant negative mutant PKR, yet enhanced by the overexpression of PKR. The TNFα and HIV RNA activators of PKR fold into compact pseudoknots that are highly conserved within the phylogeny, supporting their essential role in the upregulation of splicing. HIV provides the first example of a virus co-opting a major cellular antiviral mechanism, the activation of PKR by its RNA, to promote splicing. Full article

The observation and analysis of RNA molecules have proved crucial for the understanding of various processes in nature. Scientists have mined knowledge and drawn conclusions using experimental methods for decades. Leveraging advanced computational methods in recent years has led to fast and more accurate results in all areas of interest. One highly challenging task, in terms of RNA analysis, is the prediction of its structure, which provides valuable information about how it transforms and operates numerous significant tasks in organisms. In this paper, we focus on the prediction of the 2-D or secondary structure of RNA, specifically, on a rare but yet complex type of pseudoknot, the L-type pseudoknot, extending our previous framework specialized for H-type pseudoknots. We propose a grammar-based framework that predicts all possible L-type pseudoknots of a sequence in a reasonable response time, leveraging also the advantages of core biological principles, such as maximum base pairs and minimum free energy. In order to evaluate the effectiveness of our methodology, we assessed four performance metrics: precision; recall; Matthews correlation coefficient (MCC); and F1-score, which is the harmonic mean of precision and recall. Our methodology outperformed the other three well known methods in terms of Precision, with a score of 0.844, while other methodologies scored 0.500, 0.333, and 0.308. Regarding the F1-score, our platform scored 0.671, while other methodologies scored 0.661, 0.449, and 0.449. The proposed methodology surpassed all methods in terms of the MCC metric, achieving a score of 0.521. The proposed method was added to our RNA toolset, which aims to enhance the capabilities of biologists in the prediction of RNA motifs, including pseudoknots, and holds the potential to be applied in a multitude of biological domains, including gene therapy, drug design, and comprehending RNA functionality. Furthermore, the suggested approach can be employed in conjunction with other methodologies to enhance the precision of RNA structure prediction. Full article

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. Full article

Non-B nucleic acids structures have arisen as key contributors to genetic variation in SARS-CoV-2. Herein, we investigated the presence of defining spike protein mutations falling within inverted repeats (IRs) for 18 SARS-CoV-2 variants, discussed the potential roles of G-quadruplexes (G4s) in SARS-CoV-2 biology, and identified potential pseudoknots within the SARS-CoV-2 genome. Surprisingly, there was a large variation in the number of defining spike protein mutations arising within IRs between variants and these were more likely to occur in the stem region of the predicted hairpin stem-loop secondary structure. Notably, mutations implicated in ACE2 binding and propagation (e.g., ΔH69/V70, N501Y, and D614G) were likely to occur within IRs, whilst mutations involved in antibody neutralization and reduced vaccine efficacy (e.g., T19R, ΔE156, ΔF157, R158G, and G446S) were rarely found within IRs. We also predicted that RNA pseudoknots could predominantly be found within, or next to, 29 mutations found in the SARS-CoV-2 spike protein. Finally, the Omicron variants BA.2, BA.4, BA.5, BA.2.12.1, and BA.2.75 appear to have lost two of the predicted G4-forming sequences found in other variants. These were found in nsp2 and the sequence complementary to the conserved stem-loop II-like motif (S2M) in the 3′ untranslated region (UTR). Taken together, non-B nucleic acids structures likely play an integral role in SARS-CoV-2 evolution and genetic diversity. Full article