Secondary Structures of MERS-CoV, SARS-CoV, and SARS-CoV-2 Spike Proteins Revealed by Infrared Vibrational Spectroscopy.

All coronaviruses are characterized by spike glycoproteins whose S1 subunits contain the receptor binding domain (RBD). The RBD anchors the virus to the host cellular membrane to regulate the virus transmissibility and infectious process. Although the protein/receptor interaction mainly depends on the spike's conformation, particularly on its S1 unit, their secondary structures are poorly known. In this paper, the S1 conformation was investigated for MERS-CoV, SARS-CoV, and SARS-CoV-2 at serological pH by measuring their Amide I infrared absorption bands. The SARS-CoV-2 S1 secondary structure revealed a strong difference compared to those of MERS-CoV and SARS-CoV, with a significant presence of extended ß-sheets. Furthermore, the conformation of the SARS-CoV-2 S1 showed a significant change by moving from serological pH to mild acidic and alkaline pH conditions. Both results suggest the capability of infrared spectroscopy to follow the secondary structure adaptation of the SARS-CoV-2 S1 to different environments.

Development of a spin-label model system for investigation of protein oligomerization states

The transmembrane domains of viral proteins are highly conserved and crucial to normal viral function. Oligomeric transmembrane domains present novel opportunities for drug development, as their disruption can prevent the assembly of the virus. The Reichart lab is particularly interested in developing retro-inverso peptide inhibitors. Retro-inverso peptides are peptides using D-amino acids mirroring a region of target protein, which allows the peptide to inhibit viral assembly, but they are also significantly less likely to be catabolized by natural metabolic or immunologic processes. The efficacy of these inhibitors is governed largely by the extent to which they mirror the target protein, making highly conserved regions, such as transmembrane domains, ideal target regions for these inhibitors. The primary technique in the literature for the investigation of oligomerization states uses fluorescence spectroscopy. We are now working on developing a novel alternative system to evaluate protein oligomerization using spin-labeled peptides that are directly incorporated into the peptide sequence. Direct incorporation of the spin-label into the peptide sequence is a more powerful technique than the standard procedures used in the literature. In particular, the ability to incorporate spin labels in various positions within the protein can give novel insights into the relative depth of the protein within a membrane, which is very difficult to study using other techniques and not possible using the fluorescence technique. The transmembrane domains of proteins with known and well-characterized monomer and trimer standard oligomerization states were synthesized using an Fmoc Solid- Phase Peptide Synthesis (SPPS) procedure incorporating an Fmoc-2,2,6,6-tetramethyl-N-oxyl-4-amino-4-carboxylic acid, (Fmoc-TOAC) instead of an alanine. Direct incorporation of stable N-oxide spin labels, which can be contrasted to labeling cysteine residues after the protein synthesis, has been used for the investigation of the secondary structure of proteins for decades, but the application of this spin labeling technique to study the oligomerization states of transmembrane domains of proteins is an understudied application. The products of SPPS were analyzed using a Liquid Chromatography Mass Spectroscopy instrument and purified using High Performance Liquid Chromatography. The spin-label was then deprotected and evaluated using Electron Spin Resonance (ESR) Spectroscopy. There are two primary future directions following this research project: first, the generation of viral proteins with spin labels incorporated in different positions to determine the relative depth of each position within the membrane;second, the incorporation of spin labels into SARS-CoV- 2 proteins to develop a model for in vitro evaluation of retro-inverso peptide assembly inhibitors. -Hampden-Sydney College Office of Undergraduate Research.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

In vivo secondary structural analysis of Influenza A virus genomic RNA.

Influenza A virus (IAV) is a respiratory virus that causes epidemics and pandemics. Knowledge of IAV RNA secondary structure in vivo is crucial for a better understanding of virus biology. Moreover, it is a fundament for the development of new RNA-targeting antivirals. Chemical RNA mapping using selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) coupled with Mutational Profiling (MaP) allows for the thorough examination of secondary structures in low-abundance RNAs in their biological context. So far, the method has been used for analyzing the RNA secondary structures of several viruses including SARS-CoV-2 in virio and in cellulo. Here, we used SHAPE-MaP and dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) for genome-wide secondary structure analysis of viral RNA (vRNA) of the pandemic influenza A/California/04/2009 (H1N1) strain in both in virio and in cellulo environments. Experimental data allowed the prediction of the secondary structures of all eight vRNA segments in virio and, for the first time, the structures of vRNA5, 7, and 8 in cellulo. We conducted a comprehensive structural analysis of the proposed vRNA structures to reveal the motifs predicted with the highest accuracy. We also performed a base-pairs conservation analysis of the predicted vRNA structures and revealed many highly conserved vRNA motifs among the IAVs. The structural motifs presented herein are potential candidates for new IAV antiviral strategies.

Generation and Functional Analysis of Defective Viral Genomes during SARS-CoV-2 Infection.

Defective viral genomes (DVGs) have been identified in many RNA viruses as a major factor influencing antiviral immune response and viral pathogenesis. However, the generation and function of DVGs in SARS-CoV-2 infection are less known. In this study, we elucidated DVG generation in SARS-CoV-2 and its relationship with host antiviral immune response. We observed DVGs ubiquitously from transcriptome sequencing (RNA-seq) data sets of in vitro infections and autopsy lung tissues of COVID-19 patients. Four genomic hot spots were identified for DVG recombination, and RNA secondary structures were suggested to mediate DVG formation. Functionally, bulk and single-cell RNA-seq analysis indicated the interferon (IFN) stimulation of SARS-CoV-2 DVGs. We further applied our criteria to the next-generation sequencing (NGS) data set from a published cohort study and observed a significantly higher amount and frequency of DVG in symptomatic patients than those in asymptomatic patients. Finally, we observed exceptionally diverse DVG populations in one immunosuppressive patient up to 140 days after the first positive test of COVID-19, suggesting for the first time an association between DVGs and persistent viral infections in SARS-CoV-2. Together, our findings strongly suggest a critical role of DVGs in modulating host IFN responses and symptom development, calling for further inquiry into the mechanisms of DVG generation and into how DVGs modulate host responses and infection outcome during SARS-CoV-2 infection. IMPORTANCE Defective viral genomes (DVGs) are generated ubiquitously in many RNA viruses, including SARS-CoV-2. Their interference activity to full-length viruses and IFN stimulation provide the potential for them to be used in novel antiviral therapies and vaccine development. SARS-CoV-2 DVGs are generated through the recombination of two discontinuous genomic fragments by viral polymerase complex, and this recombination is also one of the major mechanisms for the emergence of new coronaviruses. Focusing on the generation and function of SARS-CoV-2 DVGs, these studies identify new hot spots for nonhomologous recombination and strongly suggest that the secondary structures within viral genomes mediate the recombination. Furthermore, these studies provide the first evidence for IFN stimulation activity of de novo DVGs during natural SARS-CoV-2 infection. These findings set up the foundation for further mechanism studies of SARS-CoV-2 recombination and provide evidence to harness the immunostimulatory potential of DVGs in the development of a vaccine and antivirals for SARS-CoV-2.

Clinical, Biochemical, and ATR-FTIR Spectroscopic Parameters Associated with Death or Survival in Patients with Severe COVID-19

The wide range of symptoms of the coronavirus disease 2019 (COVID-19) makes it challenging to predict the disease evolution using a single parameter. Therefore, to describe the pathophysiological response to SARS-CoV-2 infection in hospitalized patients with severe COVID-19, we compared according to survival or death, the sociodemographic and clinical characteristics, the biochemical and immunological attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectra from saliva samples and their correlation with chemometric findings. Herein, we demonstrate that ATR-FTIR spectroscopy allows the description of the events related to cell damage, such as lipids biogenesis and the secondary structure of proteins associated with lactate dehydrogenase and albumin levels. Moreover, humoral (IgM) and cellular (IFN-gamma, TNF-alpha, IL-10, and IL-6) responses were also increased in patients who died from COVID-19. Copyright © 2023 Adriana Martinez-Cuazitl et al.

Identification of consensus hairpin loop structure among the negative sense subgenomic RNAs of SARS-CoV-2.

Background: SARS-CoV-2 is the causative agent of worldwide pandemic disease coronavirus disease 19. SARS-CoV-2 bears positive sense RNA genome that has organized and complex pattern of replication/transcription process including the generation of subgenomic RNAs. Transcription regulatory sequences have important role in the pausing of replication/transcription and generation of subgenomic RNAs. Results: In the present bioinformatics analysis, a consensus secondary structure was identified among negative sense subgenomic RNAs of SARS-CoV-2. This consensus region is present at the adjacent of initiation codon. Conclusions: This study proposed that consensus structured domain could involve in mediating the long pausing of replication/transcription complex and responsible for subgenomic RNA production. Supplementary Information: The online version contains supplementary material available at 10.1186/s42269-023-01002-3.

Computational tools for aptamer identification and optimization

Aptamers are single-stranded DNA or RNA oligonucleotides that can selectively bind to a specific target. They are generally obtained by SELEX, but the procedure is challenging and time-consuming. Moreover, the identified aptamers tend to be insufficient in stability, specificity, and affinity. Thus, only a handful of aptamers have entered the practical use stage. Recently, computational approaches have demonstrated a significant capacity to assist in the discovery of high-performance aptamers. This review discusses the advances achieved in several aspects of computational tools in this field, as well as the new progress in machine learning and deep learning, which are used in aptamer identification and optimization. To illustrate these computationally aided processes, aptamer selections against SARS-CoV-2 are discussed in detail as a case study. We hope that this review will aid and motivate researchers to develop and utilize more computational techniques to discover ideal aptamers effectively. Copyright © 2022 Elsevier B.V.

Preparation of the Monoclonal Antibody against the African Swine Fever Virus p54 Protein and Identification of the Antigenic Epitope.

The aim of this paper was to prepare specific monoclonal antibody (mAb) against African swine fever virus (ASFV) p54 protein. The p54 protein was expressed in Escherichia coli expression system and used as the antigen in mAb production. The spleen cells from the immunized BALB/c mice were fused with myeloma cells SP2/0. To screen the positive hybridoma cells, the purified p54 protein was used as envelope antigen for indirect ELISA. After four times' subcloning, the supernatant of hybridoma cells were used to identify mAb subtype, ascites were prepared via in vivo induction method in mice and then the mAb was purified. The titer of the mAb was detected by indirect ELISA, and the specificity of the mAb was identified by cross reactivity assay, IFA and Western blot. According to the predicted secondary structure of p54 protein, using the stepwise truncation method identified the epitope region of mAbs, and labeled the region in tertiary structure of p54 protein. Results were as follows: six hybridoma cells secreting p54 monoclonal antibody were successfully screened and named 28G12-1, 31G7-1, 31G7-2, 35F10-1, 35F10-2, 38D3-1, respectively. The heavy chains of 28G12-1, 31G7-1, and 31G7-2 were IgG2a type, the heavy chains of 35F10-1, 35F10-2, 38D3-1 were IgG1 type, light chains were all kappa chains. The lowest titer of mAb was 1:25 600, and having no cross reaction with PRRSV, PRV, PEDV, PPV, SADS-CoV, PCV2, the specificity was strong. All six monoclonal antibodies could recognize the 127-146 aa on carboxyl end. In this study, ASFV p54 protein and p54 monoclonal antibody were successfully obtained, and the epitopes of six mAbs were identified, these experimental data laid a foundation for the functional research of p54 protein and the study of ASFV epitope vaccine. Copyright © 2023 Editorial Board, Institute of Animal Science of the Chinese Academy of Agricultural Sciences. All rights reserved.

S-PDB: Analysis and Classification of SARS-CoV-2 Spike Protein Structures

This paper proposes a novel and efficient method, called S-PDB, for the analysis and classification of Spike (S) protein structures of SARS-CoV-2 and other viruses/organisms in the Protein Data Bank (PDB). The method first finds and identifies protein structures in PDB that are similar to a protein structure of interest (SARS-CoV-2 S) via a protein structure comparison tool. The amino acid (AA) sequences of identified protein structures, downloaded from PDB, and their aligned amino acids (AAA) and secondary structure elements (ASSE), that are stored in three separate datasets, are then used for the reliable detection/classification of SARS-CoV-2 S protein structures. Three classifiers are used and their performance is compared by using six evaluation metrics. Obtained results show that two classifiers for text data (Multinomial Naive Bayes and Stochastic Gradient Descent) performed better and achieved high accuracy on the dataset that contains AAA of protein structures compared to the datasets for AA and ASSE, respectively. © 2022 IEEE.

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

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

SARS-CoV-2 Variants of Concern and Variations within Their Genome Architecture: Does Nucleotide Distribution and Mutation Rate Alter the Functionality and Evolution of the Virus?

SARS-CoV-2 virus pathogenicity and transmissibility are correlated with the mutations acquired over time, giving rise to variants of concern (VOCs). Mutations can significantly influence the genetic make-up of the virus. Herein, we analyzed the SARS-CoV-2 genomes and sub-genomic nucleotide composition in relation to the mutation rate. Nucleotide percentage distributions of 1397 in-house-sequenced SARS-CoV-2 genomes were enumerated, and comparative analyses (i) within the VOCs and of (ii) recovered and mortality patients were performed. Fisher's test was carried out to highlight the significant mutations, followed by RNA secondary structure prediction and protein modeling for their functional impacts. Subsequently, a uniform dinucleotide composition of AT and GC was found across study cohorts. Notably, the N gene was observed to have a high GC percentage coupled with a relatively higher mutation rate. Functional analysis demonstrated the N gene mutations, C29144T and G29332T, to induce structural changes at the RNA level. Protein secondary structure prediction with N gene missense mutations revealed a differential composition of alpha helices, beta sheets, and coils, whereas the tertiary structure displayed no significant changes. Additionally, the N gene CTD region displayed no mutations. The analysis highlighted the importance of N protein in viral evolution with CTD as a possible target for antiviral drugs.

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

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

Understanding the Excitation Wavelength Dependence and Thermal Stability of the SARS-CoV-2 Receptor-Binding Domain Using Surface-Enhanced Raman Scattering and Machine Learning

COVID-19 has cost millions of lives worldwide. The constant mutation of SARS-CoV-2 calls for thorough research to facilitate the development of variant surveillance. In this work, we studied the fundamental properties related to the optical identification of the receptor-binding domain (RBD) of SARSCoV-2 spike protein, a key component of viral infection. The Raman modes of the SARS-CoV-2 RBD were captured by surface enhanced Raman spectroscopy (SERS) using gold nanoparticles (AuNPs). The observed Raman enhancement strongly depends on the excitation wavelength as a result of the aggregation of AuNPs. The characteristic Raman spectra of RBDs from SARS-CoV-2 and MERS-CoV were analyzed by principal component analysis that reveals the role of secondary structures in the SERS process, which is corroborated with the thermal stability under laser heating. We can easily distinguish the Raman spectra of two RBDs using machine learning algorithms with accuracy, precision, recall, and F1 scores all over 95%. Our work provides an in-depth understanding of the SARS-CoV-2 RBD and paves the way toward rapid analysis and discrimination of complex proteins of infectious viruses and other biomolecules.

Design, production and characterization of antiviral proteins targeting SARS-CoV-2

The virus responsible for the current COVID -19 pandemic is SARS-CoV-2, which has caused >400 million infections and >5 million deaths (as of February 2022). Despite vaccination efforts, there is still an urgent need to develop strategies to control infection and treat patients. One of the proteins bound to the viral membrane is the spike (S) protein, which consists of two subunits: S1, which contains a receptor-binding domain (RBD) responsible for binding to the host cell receptor, and S2, which facilitates membrane fusion between the viral and host cell membranes, previously published in: Jackson CB et al. (2018) Nat Rev Mol Cell Biol 23, 3-20. Thus, this protein is primarily responsible for the ability of the virus to enter host cells, making it one of the most promising therapeutic targets of coronavirus, previously published in: Cao L et al. (2020) Science 6515, 426- 431. The aim of this work was to design and produce antiviral proteins that could prevent the interaction between the two proteins and thus block infection by binding to the RBD region and blocking its interaction with the host receptor, angiotensin converting enzyme-2 (ACE2) protein. First, several antiviral proteins were computationally designed using the Rosetta program based on the interactions between ACE2 and the RBD. Next, six molecular dynamics simulations (MD) of 1 ls of three candidates were performed to test their interaction with the RBD. This was followed by experimental validation after expression and purification of the three candidates. The secondary structure and thermostability of these proteins were tested by far-UV circular dichroism spectropolarimetry. Surface plasmon resonance was used to evaluate the affinity of each candidate for RBD. Neutralization assays were performed to investigate the neutralization ability of the proteins. The experimental results show that one of the developed proteins is a promising therapeutic approach that will be further improved in the future.

Plant-Based Natural Bioactive Compounds 2,4-Ditert-Butylphenolas: A Potential Candidates Against SARS-Cov-2019.

The novel coronavirus 2019 is spreading around the world and causing serious concern. However, there is limited information about novel coronavirus that hinders the design of effective drug. Bioactive compounds are rich source of chemo preventive ingredients. In our present research focuses on identifying and recognizing bioactive chemicals in Lantana camara, by evaluating their potential toward new coronaviruses and confirming the findings using molecular docking, ADMET, network analysis and dynamics investigations.. The spike protein receptor binding domain were docked with 25 identified compounds and 2,4-Ditertbutyl-phenol (-6.3kcal/mol) shows highest docking score, its interactions enhances the increase in binding and helps to identify the biological activity. The ADME/toxicity result shows that all the tested compounds can serve as inhibitors of the enzymes CYP1A2 and CYP2D6. In addition, Molecular dynamics simulations studies with reference inhibitors were carried out to test the stability. This study identifies the possible active molecules against the receptor binding domain of spike protein, which can be further exploited for the treatment of novel coronavirus 2019. The results of the toxicity risk for phytocompounds and their active derivatives showed a moderate to good drug score.

Recent advances in RNA structurome.

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

The impacts of 13 novel mutations of SARS-CoV-2 on protein dynamics: In silico analysis from Turkey

SARS-CoV-2 inherits a high rate of mutations making it better suited to the host since its fundamental role in evolution is to provide diversity into the genome. This research aims to identify variations in Turkish isolates and predict their impacts on proteins. To identify novel variations and predict their impacts on protein dynamics, in silico methodology was used. The 411 sequences from Turkey were analysed. Secondary structure prediction by Garnier-Osguthorpe-Robson (GOR) was used. To find the effects of identified Spike mutations on protein dynamics, the SARS-CoV-2 structures (PDB:6VYB, 6M0J) were uploaded and predicted by Cutoff Scanning Matrix (mCSM), DynaMut and MutaBind2. To understand the effects of these mutations on Spike protein molecular dynamics (MD) simulation was employed. Turkish sequences were aligned with sequences worldwide by MUSCLE, and phylogenetic analysis was performed via MegaX. The 13 novel mutations were identified, and six of them belong to spike glycoprotein. Ten of these variations revealed alteration in the secondary structure of the protein. Differences of free energy between the reference sequence and six mutants were found below zero for each of six isolates, demonstrating these variations have stabilizing effects on protein structure. Differences in vibrational entropy calculation revealed that three variants have rigidification, while the other three have a flexibility effect. MD simulation revealed that point mutations in spike glycoprotein and RBD:ACE-2 complex cause changes in protein dynamics compared to the wild-type, suggesting possible alterations in binding affinity. The phylogenetic analysis showed Turkish sequences distributed throughout the tree, revealing multiple entrances to Turkey.

VHH Structural Modelling Approaches: A Critical Review.

VHH, i.e., VH domains of camelid single-chain antibodies, are very promising therapeutic agents due to their significant physicochemical advantages compared to classical mammalian antibodies. The number of experimentally solved VHH structures has significantly improved recently, which is of great help, because it offers the ability to directly work on 3D structures to humanise or improve them. Unfortunately, most VHHs do not have 3D structures. Thus, it is essential to find alternative ways to get structural information. The methods of structure prediction from the primary amino acid sequence appear essential to bypass this limitation. This review presents the most extensive overview of structure prediction methods applied for the 3D modelling of a given VHH sequence (a total of 21). Besides the historical overview, it aims at showing how model software programs have been shaping the structural predictions of VHHs. A brief explanation of each methodology is supplied, and pertinent examples of their usage are provided. Finally, we present a structure prediction case study of a recently solved VHH structure. According to some recent studies and the present analysis, AlphaFold 2 and NanoNet appear to be the best tools to predict a structural model of VHH from its sequence.

RNA Secondary Structure Database, Analysis Tool-Set, and Case-Study Results on SARS-CoV-2

COVID-19 pandemic has brought immense attention to SARS-CoV-2 and related microbiology studies. To defeat this deadly virus, its RNA is being studied by many researchers around the globe. This study primarily aims to compile a large RNA dataset to analyze RNA secondary structure of SARS-CoV-2 efficiently. We propose improvements on database creation and maintenance, and structure analysis tools. As a continuation of our previous works, we automate the creation of RNA secondary structures database in a new format by converting data collected from publicly available online resources. We present new secondary structure analysis algorithms that improve performance of existing tools. Results of GPU-based implementation are also presented for RNA search operations. We also introduce tools with new objectives, which answer fundamental RNA secondary structure queries. Our tools on the current database have been tested with SARS-CoV-2 related RNA secondary structures. A novel RNA secondary structure search-based multiple RNA comparison is introduced and tested too. Structural-only and structure-with-nucleotide search results particularly related to SARS-CoV-2 are presented in details. As a successful case study, the framework presented here offers some unique capabilities and is shown as a useful exploratory tool for future RNA analysis studies. © 2021 IEEE.

Secondary Structure of Influenza A Virus Genomic Segment 8 RNA Folded in a Cellular Environment.

Influenza A virus (IAV) is a member of the single-stranded RNA (ssRNA) family of viruses. The most recent global pandemic caused by the SARS-CoV-2 virus has shown the major threat that RNA viruses can pose to humanity. In comparison, influenza has an even higher pandemic potential as a result of its high rate of mutations within its relatively short (<13 kbp) genome, as well as its capability to undergo genetic reassortment. In light of this threat, and the fact that RNA structure is connected to a broad range of known biological functions, deeper investigation of viral RNA (vRNA) structures is of high interest. Here, for the first time, we propose a secondary structure for segment 8 vRNA (vRNA8) of A/California/04/2009 (H1N1) formed in the presence of cellular and viral components. This structure shows similarities with prior in vitro experiments. Additionally, we determined the location of several well-defined, conserved structural motifs of vRNA8 within IAV strains with possible functionality. These RNA motifs appear to fold independently of regional nucleoprotein (NP)-binding affinity, but a low or uneven distribution of NP in each motif region is noted. This research also highlights several accessible sites for oligonucleotide tools and small molecules in vRNA8 in a cellular environment that might be a target for influenza A virus inhibition on the RNA level.