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. 2025 Jul 1;10(27):29408–29420. doi: 10.1021/acsomega.5c02568

SARS-CoV‑2 RNA’s Dual Identity: G‑Quadruplex versus Hairpin

Alex Nyporko a, Ivan Voiteshenko a,b, Margarita Zarudnaya b, Vasyl Hurmach b, Tetiana Shyryna b, Maksym Platonov b, Szczepan Roszak c, Bakhtiyor Rasulev d, Leonid Gorb b,*
PMCID: PMC12268457  PMID: 40687000

Abstract

Regardless of advances in biophysical assays for studying G-quadruplexes formation, their high-resolution structural characterization remains limited. In this computational study, the 2D and 3D geometry, energetics, and dynamics of the SARS-CoV-2 potential quadruplex at position 28903 were studied. Two- and three-dimensional structures for four G4-Quadruplexes and three hairpins were predicted using bioinformatics tools. The dynamics, relative stability, impact, and presence of a pseudouridine site were examined in detail. It was hypothesized that the dynamic stability of G4-quadruplexes critically depends on the number of Hoogsteen connections, which stabilize the G4-quadruplex structure. It was also shown that the presence of pseudouridine colocalized with potential quadruplex at position 28903 could enhance the dynamic stability of hairpins and destabilize the structure of G4-quadruplex up to direct unwinding.

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Introduction

Despite numerous studies, the number of drugs capable of directly targeting viruses and their components remains extremely limited. This situation highlights the insufficient effectiveness of existing methodological approaches in antiviral drug development. While a complete revision of the rational drug design paradigm may not be necessary, expanding the range of molecular targets whose disruption is critical to the viral life cycle is essential. In the case of RNA viruses, particularly SARS-CoV-2, putative G-quadruplex (G4)-forming sequences (PQSes) have emerged as highly promising targets. − RNA (and DNA) G-quadruplexes are noncanonical nucleic acid structures formed by guanine-rich sequences. G4s contain two or more layers of G-quartets, where four guanines interact via Hoogsteen-type base pairing.

These structures play a significant role in regulating gene expression. − G-Quadruplexes are widely found in DNA promoter regions as well as in the untranslated regions (UTRs) and gene bodies of mRNAs, where they impact both transcriptional and posttranscriptional processes. In the 5′ UTR, G4 structures can regulate translation efficiency by obstructing ribosome scanning. As demonstrated by Bugaut and Balasubramanian, the presence of G4s reduces translation initiation rates, a regulation mechanism that becomes particularly crucial when fine-tuning protein synthesis is necessary for cellular responses to stress or environmental changes. Additionally, G4s in the 3′ UTR of mRNAs can affect mRNA stability and localization, thereby influencing gene expression at a posttranscriptional level. , By modulating RNA stability, G4s enable cells to regulate the half-life of specific transcripts, dynamically adjusting the proteome in response to various stimuli.

Notably, G-quadruplexes (G4s) have been implicated in the regulation of both oncogenes and tumor suppressor genes, making them promising therapeutic targets in cancer. In particular, stabilizing G4 structures can inhibit the expression of oncogenes such as KRAS and c-MYC or enhance the stability of tumor suppressor transcripts, offering dual therapeutic potential. Due to the functional dynamics of G4s, novel therapeutic strategies have emerged, as targeting these structures with small-molecule ligands has shown promise in modulating gene expression in cancer cells. , Researchers have demonstrated that G4 stabilization can reduce cancer cell proliferation, making them attractive candidates for drug development targeting oncogenic pathways. Furthermore, the interaction between G4 structures and the cellular environment is critical to their function. Factors such as ion concentrations and the presence of specific ligands can stabilize or destabilize these structures, thereby altering their regulatory impact.

Regardless of advances in biophysical assays for studying G-quadruplexes formation, their high-resolution structural characterization remains limited. A deeper structural understanding of G4s could elucidate their functional mechanisms and aid in the design of more selective ligands. As therapeutic targets, G-quadruplexes should, in theory, exhibit a highly conserved spatial structureunlike proteins in RNA viruses, whose spatial features change rapidly due to the high mutability of protein-coding regions in RNA virus genomes. Approximately 50 PQSes have been identified in the positive RNA strand of the SARS-CoV-2 genome, with 37 reported in Zhai et al. review and 10 more identified in Bezzi et al. study. The formation of G-quadruplexes has been experimentally confirmed for 25 PQSes using multiple techniques. ,− In our previous work, we explored the folding of the PQS at position 3467 of the SARS-CoV-2 genomic RNA using various computational tools to generate two-dimensional structures, which were subsequently transformed into three-dimensional models. We then analyzed their geometry, energetics, and dynamics using full-electron quantum-chemical calculations and classical molecular dynamics simulations.

In this study, we focus on the structural and thermodynamic features of PQS at position 28903 (further, PQS 28903), which is capable of forming a G-quadruplex and/or hairpin structures in the SARS-CoV-2 genome RNA. The G-quadruplex derived from this sequence is the shortest known in the genome, consisting of only 15 nucleotides. Consequently, its spatial structure is expected to be highly compact, making it a promising target for drug development. Given its potential significance, we aim to reconstruct different spatial variants of PQS 28903 and evaluate their in vitro probabilities of formation by using various in silico approaches. The study begins with a bioinformatics analysis of PQS 28903, followed by a reconstruction of its possible 3D structures and further application of molecular dynamics and quantum-chemical approaches. Since pseudouridine (Ψ) (the most abundant RNA modification found in different types of RNA) is localized in close proximity to PQS 28903 at position 28927, the study is ended by the investigations of the impact of its presence in the structure of G-quadruplexes.

Materials and Methods

Bioinformatics Analysis of the SARS-CoV-2 Genome

From the GISAID database (gisaid.org), which contains a total of 17,061,756 records for the SARS-CoV-2 genome as of November 2024, 105,457 genome sequences were obtained for analysis. The sequences identified were from five countries of different continents over a five-year period. The maximum number of genomes from one country in one year was limited to the 10,000 most complete genomes, as defined by GISAID: genomes >29,000 bp are complete and then assigned a high coverage label of <1% Ns (undetermined bases). Matching, conservation, and the actual search for changes and mutations for PQS 28903 were done using the author’s software algorithm implemented in Python.

RNA Secondary Structure Prediction and Representation

The different variants of the secondary structure of the SARS-CoV-2 RNA domain containing PQS 28903 (GGcuGGcaauGGcGG) were predicted by the UNAFold program (Unified Nucleic Acid Folding). The secondary structure of certain hairpins at different temperatures were predicted by the Quikfold program (http://www.unafold.org/Dinamelt/applications/quickfold.php).

The sequence of the domain in SARS-CoV-2 genomic RNA containing PQS 28903 (taken from the SARS-CoV-2 NCBI Reference Sequence, ACCESSION NC_045512) is presented below. The beginning and the end of the domain are marked by green color, and the Ψ-site is marked in blue.graphic file with name ao5c02568_0014.jpg

Reconstruction of the Initial RNA Spatial Structure

Two variants of three-dimensional structures of SARS-CoV-2 PQS 28903 forming G-quadruplexes (Q1 and Q2), as well as three variants of hairpins formed by this PQS (H1, H2 and H3), were obtained using the web services 3D-NuS (uses existing X-ray and NMR data of databases to predict the 3D structure of RNA, including the structure of quadruplexes) and RNAComposer (uses existing X-ray and NMR data of databases to predict the 3D structure of RNA).

Also, G-quadruplexes entitled Q3 and Q4 were reconstructed via the protocol described by Miclot et al. The structural alignment of the considered G-quadruplexes is drawn in Figure .

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Structural alignment of G-quadruplexes in Q1 (green), Q2 (blue), and Q3 and Q4 (both pink). Two quadruplex models (Q1 and Q2) contained, in addition to the Hoogsteen pairing of guanine bases, Watson–Crick-like interactions. This was achieved by a 180 degree rotation of guanines at positions 11 and 12 around the C1*–N9 bonds. These structures were reconstructed to clarify the dependence of the stability of the G-quadruplex on the pattern/distribution of hydrogen bonds within it. The following two models (Q3 and Q4) contained only Hoogsteen-type interactions, which are canonical for this type of structure.

Optimization of Spatial Geometry with Quantum-Chemical Approaches

Quantum-chemical calculations were conducted using the Gaussian 16 software at the level of the electron density functional theory, incorporating dispersion interactions. The exchange and correlation functionals B97-D3 and the 6-31G (d,p) basis set were employed. Both tools are well known for providing a balance between computational time and resource efficiency while maintaining quality for large systems. The tools also were utilized for computational studies of systems such as d­(A)5·d­(T)5 and d­(G)5·d­(C)5. However, due to the large size of the system (the smallest RNA fragment contained 490 atoms and 5756 basis functions), soft convergence criteria [opt = Loose and IOp­(1/18 = 100,000)] were applied to reduce the number of redundant internal coordinates.

The influence of the water environment was taken into account by applying the conductor-like polarizable continuum model (CPCM) approximation (dielectric continuum with dielectric constant ε = 78.3). , The presence of counterions that compensate for the charge of the RNA backbone in the CPCM approximation is taken into account automatically through the interaction with a positively charged molecular cavity. However, the RNA fragments were also considered when a single K+ or Na+ counterion was inserted into a quadruplex structure or when they were presented explicitly as interacting with RNA backbone counterions. In the latter case, the location was chosen randomly.

Analysis of Electron Density Distribution

The analysis of electron density distribution has been performed with the application of the AIMALL package at the B97-D3/6-31G­(d,p) level of theory. The presence of a critical bond point (BCP) of the (3, −1) type and a positive Laplacian value in this BCP (Δρb > 0) were considered as criteria for the formation of the hydrogen bond. The energies of hydrogen bonds are calculated based on the empirical method of Espinoza–Molins–Lecomte (EML): E AH···B = 0.5·V(r), where V(r) is the value of the local potential energy at the critical point of (3, −1) type.

Classical Molecular Dynamics Calculations

Ensembles of conformations of SARS-CoV-2 genomic PQS 28903 were calculated using two different protocols to avoid aberrations conditioned by special bugs/features characterized by one or other software. According to the first protocol, ensembles of conformations were obtained by molecular dynamics (MD) calculations with AMBER22 software , using OL3 force field, Amber series’ force field specialized for RNA dynamics computations. A cubic box with a 1.2 nm distance between the edge and the nearest RNA atom and a TIP3 water model was used to reproduce the molecular environment according to the experimental conditions. Each RNA structural variant was calculated at 293.15 and 309.75 K and 150 mM concentrations of either Na+ or K+ ions. Energy minimizations of all investigated systems were realized via the steepest descent algorithm, after that they were equilibrated within 0.5 ns intervals from initial 273 K to target temperatures using a Langevin thermostat. The same thermostat and Monte Carlo barostat were used during the next productive MD simulations.

The second protocol included MD calculations with GROMACS 2021 software using the Charmm36 force field. Computation details can be found in authors previous publication.

Free Energy Estimation

The free energies for the RNA conformation ensembles obtained from MD calculations were calculated using the standard energy operand in GROMACS. The reference temperature for the free energy estimation corresponded to the temperature during the MD simulation. Principal component analysis (PCA) has been applied to identify and explain large-scale coordinated movements within the structures formed by SAR-CoV-2 PQS 28903.

The simulations were performed using eigenvectors obtained from the mass-weighted covariance matrix of RNA atomic fluctuations. The build-in GROMACS function “gmx covar” was employed to generate the covariance matrix, using the representative RNA structure from the MD simulation as a reference to evaluate rotation fit during the MD trajectory. Subsequently, to define the dimensionality of the essential subspace, eigenvectors and eigenvalues were calculated. Importantly, most of the movements (∼90%) can be characterized using <10 eigenvectors, which reveal the significant coordinated motions occurring within an atomic system. Cosine content is used as a measure of principal components. − If the cosine content is close to 1, it indicates significant movement within the RNA molecule and renders it unsuitable for PCA. However, most snapshots captured during MD simulation exhibit cosine values close to 0.2, with some approaching 0.5, making them suitable for PCA. So, according to the above, by using “gmx analyze”, utility FEL (free energy landscape) was constructed utilizing cosine contents <0.2 of the first two projection eigenvectors (defined as PC1 and PC2, respectively). In the current case, PC1 and PC2 are based on RMSD values. By estimating how structures deviate from a reference structure, it is possible to conclude whether the investigated structure is stable or not (by that, we can refer to the definition of Gibbs free energy). Based on above, it is possible to make assumptions that the conformations with lower Gibbs free energy correspond to structures that have smaller deviations in correspondence to the relevant structures. The most prevalent and energetically favorable structures extracted from the FEL’s minimum energy basins were then utilized for subsequent analyses.

Three-dimensional structures were visualized by the Mol* and PyMol molecular graphic programs. Two-dimensional structures were visualized by the forna and MINT.

Results and Discussion

PQS 28903 is located in gene N in the second hairpin of a relatively small domain both in genomic RNA (gRNA) and mRNA of N protein. , UNAFold program predicts (Figure A) a similar structure of this domain in mRNA as in Zhao et al. The optimal structure in gRNA predicted by UNAFold (Figure B) differs from that in Sun et al. Only suboptimal folding with the energy increment of the lowest change in free energy (ΔΔG) of 2.4 kcal/mol is similar to this model.

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Secondary structure prediction of the domain containing PQS 28903 in the SARS-CoV-2 genome Wuhan-Hu-1 (accession number NC_045512, reference genome). ΔGthe change in free energy against the disordered RNA structure. (A) Domain in N mRNA. (B) Domain in gRNA. (C) Domain in gRNA with triple mutation. Positions of the PQS and Ψ-site in gRNA are 53–67 and 77, respectively.

According to Razzaq et al. who analyzed mutation rates of SARS-CoV-2 PQSes in more than 14 million genome sequences for 10 clinically reported variants, PQS 28903 is one of the few sites, which are prone to mutations. In this study, the search was performed for mutations in about 100,000 SARS genomes separately for each country and year (for 5 countries, from 2020 to 2024) (see Table S1). The search was performed not only directly in PQSes as in Razzaq et al. work but also in the self-contained RNA structures containing them. In addition, we found (Table S1) that mutations directly in G repeats of PQS occurred in 2021 and 2022 years with high frequency (up to 96%). They destroyed G4 28903. However, such mutations have not already occurred in 2023 and 2024 years that supports functional significance of this G-quadruplex. Also, we showed that the triple mutation G31A+G32A+G33C that has occurred with different frequency since the beginning of the epidemic become dominant in last years. It results in alteration of G4 28903 location; now it locates in two short hairpins (Figure C). This mutation increased the probability of G-quadruplex formation inside the domain by decreasing stability of the minimal structural element containing PQS by 3.3 kcal/mol (Figure S1).

Another fact that supports the significance of G4 28903 is the existence of its analogue in the SARS-CoV genome. Moreover, this analogue (PQS 28752 in this genome) is located in a similar mRNA domain (Figure A). It has different locations of the second GG repeat in PQS and different loops (Figure B) and forms a less stable hairpin than PQS 28903 (Figure C,D).

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Secondary structure prediction of the domain containing PBS 28752 in SARS-CoV, the hairpin formed by it, and the hairpin formed by PQS 28903 in SARS-CoV-2. (A, C) SARS-CoV genome Tor2 (accession number NC_004718). (B) Alignment of PQSes in SARS-CoV-2 and SARS-CoV genomes. (D) SARS-CoV-2 genome Wuhan-Hu-1 (accession number NC_045512). ΔGthe change in free energy.

The formation of the G4 structure by PQS 28903 was studied in a number of works. Most authors confirmed its formation, ,,− while authors of refs , , and did not confirmed it. Recently, Gupta et al. demonstrated that PQS 28903 exists in hairpin-G-quadruplex conformational equilibria. In addition, Wang et al. showed that PQS 28903 can form dimeric quadruplex, while Campanile et al. demonstrated that this PQS forms a monomolecular G-quadruplex at the temperature 0 °C in agreement with a model of Miclot et al.; however, under physiological conditions, its dominant conformation is stable RNA G-triplex composed of two G-triads. Notably, the formation of unimolecilar G4, dimeric G4, and G-triplex by PQS 28903 was demonstrated both in vitro and in cell. − The formation of a tetrameric quadruplex by PQS 28903 in cell also cannot be excluded since the nucleocapsid protein gene is a part of all eight SARS-CoV-2 subgenomic RNAs. Zhao et al. estimated that ΔG0 (25 °C) for G4 formation is −2.6 kcal/mol according to the melting measurements. Also Zhao et al. found that ΔG for hairpin formation by PQS 28903 at this temperature (25 °C) is −3.9 kcal/mol (Figure ), i.e., formation of the hairpin is more preferable than the formation of G-quadruplex. At 37 °C, the hairpin has the same structure. Its ΔG = −2.3 kcal/mol, which is slightly higher than the value predicted by the UNAFold program, and the stems of the hairpins predicted by these programs have different lengths. The values of ΔG for G4 28903 are not known at 37 °C and other temperatures. However, its stability can be increased in cell, for example, by crowding agents. Since PQS 28752 in the SARS-CoV genome forms the hairpin with ΔG = 0.0 kcal/mol, it will compete with G4-quadruplex formation to considerably less extent than the hairpin in SARS-CoV-2.

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Secondary structure prediction of PQS 28903 in SARS-CoV-2 genome Wuhan-Hu-1 (accession number NC_045512) at 25 °C. ΔGchange of free energy.

Findings about G-quadruplex formation by PQS 28903 by different authors can be explained by special experimental conditions, in particular, the PQS concentration. Unlike other authors, the authors of works, refs and , used low concentrations of oligonucleotides in their CD, NMR, and TDS assays. At such concentrations, oligonucleotides might fold on themselves rather than interact with other strands. At high concentrations, their interaction with each other with the formation of multimolecular G-quadruplexes (in particular, from 4 strands) might be preferable to the formation of hairpins, and just the formation of multimolecular structures instead of unimolecular G4s may be observed in some works. Exposure of one or two GG-repeats in the hairpin structures (as in Figures and ) might facilitate the formation of multimolecular structures.

One should mention that the available literature data are clearly insufficient to draw reasonable conclusions about the structure of the quadruplex formed by PQS 28903, which is extremely important for the subsequent search for/development of drugs targeting this G4, nor about its stability over time or the quantitative relationship between the hairpin and the quadruplex. To partially fill this data gap up, in the next phase of the study, we reconstructed different variants of the spatial structure of PQS 28903, which included several of both the quadruplex and the hairpin and their investigated properties using quantum mechanics and molecular dynamics approaches.

The number of publications devoted to studying time stability and evolution of genomic SAR-CoV-2 PQSes is minimal. This issue is covered, in particular, in the articles of Miclot et al. (study of behavior of viral G4-quadruplex RG-1 (G4 28903) itself and in complexes with low-weight molecular compounds via molecular dynamics), D’Anna et al. (similar investigation of viral G4-quadruplex RG2 (G4 at position 13385), D’Anna et al. , (research on behavior of mRNA coding for the transmembrane serine protease 2 TMPRSS2), and Razzak et al. (G4 at position 3467).

All of them are focused namely on G-quadruplex conformation and did not pay attention to alternative structural possibilities, which seem to be incomplete, especially concerning the conformational space of RG-1, for which the ability to exist in a hairpin conformation was demonstrated.

The scheme of the hydrogen bond distribution within the structures forming by PQS is shown in Figure . As can be seen from the presented data, the hairpin H1 contains two canonical complementary guanine-cytosine pairs forming three hydrogen bonds each; this variant of the structure also contains two noncanonical guanine-uracil pairs forming one hydrogen bond each. Two remaining variants (the hairpin H2 and H3) also form two canonical complementary “guanine-cytosine” pairs each, but unlike the hairpin variant, H1 contains only one “guanine-uracil” pair.

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Analysis of the interactions using the MINT toolkit of the optimized investigated structures. The colors indicate the number of hydrogen bonds from their absence in blue to the maximum 2–5 (depending on the structure) in red. In this case, Watson–Crick-like bonds are additionally marked separately by lines connecting nonsequential nucleotides. Dot-bracket symbols correspond to the starting structures that were further optimized.

As was already mentioned, a number of experimental studies demonstrate that PQS 28903 of SARS-CoV-2 genomic RNA can exist in both hairpin and quadruplex conformations. Therefore, first of all, the dynamic stability of the structures considered were verified. The results of visual inspection of molecular dynamics trajectories indicate that Q1 and Q2 structures, regardless of the molecular mechanical engine used in the force field, and the conditions under which the behavior is simulated, undergo significant structural changes during the first 30–50 ns of molecular dynamics, accompanied by displacement of the coordinating potassium ion and disintegration of the quadruplex (see Figure S2). The formation of hairpin-type structures in this case is not observed in the case of both 250 ns of molecular dynamics and in the case of continued calculations up to 5 μs. Therefore, except for very limited cases, we did not investigate those structures at the quantum-chemical level.

At the same time, the Q3 and Q4 quadruplexes retain intact quadruplexes during the 5 μs intervals, and the spatial geometry of these SARS-CoV-2 RNA variants fluctuates very insignificantly (see also Figure S3 for the view of the Q3 and Q4 geometry after 500 ns of MD simulations). The corresponding RMSD profiles for the Charmm36 force field are presented in Figure S4. The final geometries of the studied RNA conformation are shown in Figure .

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Spatial structure of Q3 and Q4 variants of PQS 28903 G-quadruplexes after 5 μs molecular dynamics simulations within the OL3 force field.

All three investigated hairpin variants (H1, H2, and H3) maintained their conformation during 250 ns of molecular dynamics (H1 maintained its conformation during the special test, which lasted 5 μs) during all combinations of temperature and ionic composition of the environment and did not show any tendencies to unravelling or transition to other variants of the structure.

The application of Principal Component Analysis suggests (see Figure ) the existence of a highly stable hairpin structure, with the Gibbs free energy of all configurations lying in the interval between 3.0 and 4.5 kcal/mol. In almost all cases, the conformational space of the investigated hairpins is limited by just one conformation. The only exception is H2 simulated at 300 °K; here, two possible conformations can be obtained during the MD simulation.

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Hairpin’s free energy landscapes (FEL) for systems with SOD atoms, 293°K (A–C) and 30 °C (D–F). H1 (A, D), H2 (B, E), and H3 (C, F).

The RMSD differences for all of the aligned snapshots of the MD simulation of the investigated hairpin RNA structures in each trajectory are within 2Å. Such a result suggests that the studied RNA structures instantly find their energy minimum and remain there throughout the entire length of the MD simulation. This conclusion is supported by the fact that RNA structures H1, H2, and H3 have similar RMSD values of within 0.2–0.3 nm. The reason for this is probably because all nucleotides actively participate in the hairpin formation in all of the hairpins investigated.

Data presented in Tables and display another important characteristic of quadruplexes and hairpins: relative stability. The optimized relative energies at the quantum-mechanical level of considered G-quadruplexes and hairpins are shown in Table . Table collects the relative Gibbs free energies obtained by averaging the spatial geometries of the corresponding MD ensembles at different force fields.

1. Relative Energies (kcal/mol) of the Structures Formed by PQS 28903 with Different Geometries Obtained at the Quantum-Mechanical Level .

  initial geometry
 MD averaged geometry
parameter water solution, ionic atmosphere K+ Na+ water solution, ionic atmosphere K+ Na+
H1 47.70 66.50 59.79 34.3 88.35 86.69
H2 48.15 80.78 82.70 7.31 68.16 60.46
H3 55.07 82.80 84.94 0.00 0.00 0.00
Q3 1.36 13.85 10.43 14.69 19.80 15.57
Q4 0.00 0.00 0.00 23.38 77.43 63.02
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a

Water solution, ionic atmosphere, and explicit cation of K+ located in the central part of G-quadruplex to stabilize the structure.

b

Water solution, ionic atmosphere, and explicit cation of Na+ located in the central part of G-quadruplex to stabilize the structure.

c

The data are not available because of dynamic instability of the corresponding species.

2. Relative Gibbs Free Energies (kcal/mol) of the Structures Formed by PQS 28903 with Different Geometries Obtained by Averaging the Spatial Geometries of the Corresponding Molecular Dynamic Ensembles at Different Force Fields.

  NaCl
KCl
  temperature °K
parameter 293 310 293 310
H1 0 (6.68) 0 (2.07) 6.96 (0) 0 (0)
H2 5.84 (0) 1.55 (0) 0 (20.59) 12.97 (8.22)
H3 12.3 (29.04) 0.81 (31.67) 37.61 (19.06) 12.97 (18.48)
Q3 80.07 (81.59) 67.89 (40.52) 58.54 (17.06) 86.7 (48.49)
Q4 50.17 (87.03) 42.03 (56.62) 34.88 (22.05) 38.23 (64.58)
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a

1.2 nm cubic box of water molecules, 150 mM concentrations of either NaCl or KCl.

b

OL3 force field.

c

Charmm36 force field.

We understand the data collected in Tables and as the manifestation of the situation observed experimentally and described above. Namely, as a structural type, both G-quadruplexes and hairpins formed by PQS 28903 of SARS-CoV-2 genomic RNA are thermodynamically stable and located in deep minima of the potential surface. However, the dominance of one of them critically depends on experimental conditions, which are regulated by the presence of counterions, various proteins, and other factors. In other words, in vivo, transitions of the quadruplex formed by PQS 28903 into a hairpin and back are prevented by high energy barriers. Nevertheless, those transitions (if, of course, they take place) may either be provided by interaction with protein/other RNA molecules or require very long time intervals. , So, these results support the idea that folding of the PQS 28903 of the SARS-Cov-2 genomic RNA can be considered as an example of multipathway RNA folding, where interactions mentioned above play a crucial role by binding and stabilizing certain elements of the RNA structure and driving the folding in different ways. ,,

It is generally accepted that the geometrical structures of DNA and RNA are mostly stabilized by stacking and hydrogen bonding interactions. Surprisingly, the application of the MINT bioinformatic tool resulted in a very low contribution, originating from stacking interactions (3.7 and 54.6 kcal/mol for Q4 and Q3, respectively). The reason for this phenomenon is what we plan to study separately. This publication presents two results based on the analysis of the characteristics of intramolecular hydrogen bonds using the theory of atoms in molecules (see Figures , Figure S5, and Table ). The data collected indicate the presence of a network of intramolecular hydrogen bonds for all investigated species. In the case of Q3 and Q4 G-quadruplexes, the network has a number of hydrogen bonds, which virtually do not depend on the presence of compensating ions. However, the amount of hydrogen bonds in Q3 and Q4 is different compared to the amount in the hairpins. We guess that such a network has an important impact on the maintenance of the structure and that future ligands (antiviral drugs) should be aimed at rebuilding the structure at the sites of the strongest hydrogen bonds. It is also important to mention that, during the investigation in PQS 3467 in SAR-CoV-2 RNA, the similar network was found.

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Spatial distribution of hydrogen bonds in different G-quadruplex variants.

3. AIM Analyses of Hydrogen Bonds in G-Quadruplexes and Hairpins .

  anion
 K+
Na+
name Σ EAH···B, kcal/mol Num EAH···B Avg EAH···B Σ EAH···B, kcal/mol Num EAH···B Avg EAH···B Σ EAH···B, kcal/mol Num EAH···B Avg EAH···B
H1 400.57 110 3.64 392.34 114 3.44 404.74 108 3.75
H2 396.78 106 3.74 426.36 123 3.47 422.07 119 3.55
H3 387.44 112 3.46 372.98 106 3.52 382.38 109 3.51
Q3 464.00 128 3.62 453.15 131 3.49 463.12 128 3.62
Q4 459.73 131 3.51 467.02 134 3.46 471.95 133 3.55
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a

We do not consider Q1 and Q2 structures because they are dynamically unstable according to MD simulations.

b

Water solution, ionic atmosphere, and explicit cation of K+ located in the central part of G-quadruplex to stabilize the structure.

c

Water solution, ionic atmosphere, and explicit cation of Na+ located in the central part of G-quadruplex to stabilize the structure.

A fascinating insight into the geometric and electronic structure of the considered quadruplexes is provided by the data presented in Table . It was found that the geometrical structure of Q2 is stabilized by quite an unusual type of hydrogen bond, which we call Watson–Crick-like ones. Two guanines located in different G-tetrads interact with one another in the same way as guanine interacts with cytosine in regular DNA or RNA (see Figure ). It is important to note that such types of hydrogen bonds remain stable after quantum-mechanical optimization of the quadruplex geometry.

4. Composition of Hydrogen Bonds That Stabilize Tetrads in the Studied Quadruplexes, the Designation of Atoms Is the Generally Accepted Nomenclature for RNA .

graphic file with name ao5c02568_0012.jpg

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Cell colorthe appropriate relationship is unique to the color-matched Q. Boldthe bond is present in all studied Q1–Q4. Italicsthe bond is common for Q1 and Q2. Underlined fontthe bond is common for Q2 and Q3, Q4. Underlined italicsthe bond is common for Q3 and Q4 only.

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Watson–Crick-like type of hydrogen bonding in the Q2 G4-quadruplex (G11 and G12 coordinated with G1 and G2). Two of the six Watson–Crick-like hydrogen bonds accumulate a total of 11.03 kcal/mol.

The aforementioned factors can explain the reasons why G-quadruplexes Q1 and Q2 are dynamically unstable. As one can see from the data presented in Table , quadruplexes Q3 and Q4 have the most possible set of Hoogsteen connections in the amount of eight per tetrad. So, eight hydrogen bonds contribute to the stability of the G3 and Q4 structures as quadruplexes. At the same time, the most energetically stable quadruplex Q4 has a lower total energy compared to Q3. Also, Q3 has additional bonds with the phosphate group of the backbone of another nucleotide within the quadruplex (namely, N2G1–H22G1...O2PG5, N2G5–H22G5...O2PG11 for a single tetrad and N2G12–H22G12...O1PG15, N2G2–H22G2...O2PG6 for another one). In contrast, the quadruplexes Q1 and Q2 have just two and three Hoogsteen connections and 4 and 6 Watson–Crick-like ones correspondingly. We guess that this fact could be the reason why their structures are dynamically unstable.

It should also be noted that the reason for the dynamic instability of Q1 is completely different. Having at the beginning of geometry optimization the largest distance between bases inside the tetrads, this quadruplex loses the planarity of the tetrads (Figure ) after the optimization. The bases of G12 and G15 lose their planarity in relation to each other, which vividly emphasizes the very atypical bonds with the sugar residue G12: C2*G12–H2*G12...O6G15 and O2*G12–H2*G12... N7G15.

Talking about different structural and energetic aspects of PQS 28903 in SARS-CoV-2 genomic RNA, we cannot ignore the presence of a colocalized pseudouridine site (Ψ) in its genome. As we already mentioned above, pseudouridine is the most abundant modification, found in different types of RNA. According to Fleming et al., it is localized in close proximity to PQS 28903 at position 28927. Ψ can impact multiple cellular processes, in particular translation. − Also, Ψ-sites in SARS-CoV-2 genome may be used to avoid immune response or/and be essential for virus replication.

Ψ-site 28927 is located together with PQS 28903 in the same long hairpin (in the internal loop UG x UC, Figure A) in the domain without mutations and in the bottom base pair of the second short hairpin in the domain with the dominant triple mutation (Figure C). Colocalization of Ψ site with G4, like colocalization of m6A site with G4, may play a certain role in virus replication and even a synergistic effect is possible.

To verify the influence of pseudouridine on the structure and stability of the long hairpin containing PQS 28903, structural variants of the SARS-CoV-2 genomic RNA fragment (nucleotides 28903–28938) with uridine or pseudouridine at position 28927 were analyzed.

In this work, two orientations of pseudouridine inside of the PQS 28903 called Ψ and Ψ180 (see Figure for the details) were used. Then, Q, QΨ, H, HΨ 3D structures originated from the sequence ggcuggcaauggcggugaugcugcu­(Ψ)­cuugcuuugcu were created and verified as described below.

10.

10

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Orientation of uridine and pseudouridine inside of the long hairpin containing PQS 28903. Ψpseudouridine with the same value of the glycosidic torsional angle as in replaced uridine; Ψ180pseudouridine is rotated by 180° around the glycosidic bond. All other geometric characteristics did not change.

MD simulations of over 250 ns were performed, and free energy estimations are summarized in Table . Initially, the influence of pseudouridine appears ambiguous: it increases the free energy of the studied fragment without G4 and variants containing Q3 of PQS 28903 but decreases the free energy of the fragment with unstable Q2 and variably affects Q4. Direct pseudouridine increases Q4 energy, while inverted pseudouridine reduces it.

5. Free Energies (kcal/mol) of Different Structural Variants of SARS-CoV-2 RNA Segments 28903–28939 without/with Pseudouridine at Position 28927 and Appropriate PQS 28903 Variants?

variant full-size segment PQS 28903 PQS 28903 RMSD, Å
Q4Ψ –5067.56 –1973.83 9.5
Q4Ψ180 –5082.99 –2021.87 6.5
Q4 –5076.24 –2052.79 4.3
Q3Ψ –5095.48 –2050.97 4.5
Q3Ψ180 –5077.11 –2050.97 4.6
Q3 –5130.02 –2101.56 4.4
Q2Ψ –5077.58 –2032.19 6.6
Q2 –5068.06 –1959.63 7.4
HΨ –5157.80 –1987.91 3.0
H –5185.72 –1984.32 3.1
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It was found that pseudouridine colocalization significantly decreases the free energy and standard deviation of H and Q2, indicating their structural stabilization. However, it increases the free energy and RMS deviation of Q3 and Q4, suggesting potential destabilization of G4-quadruplexes. It is interesting to note that quadruplex Q3 remains time-stable with or without pseudouridine. Conversely, Q4 is destroyed by pseudouridine with direct conformations leading to direct unwinding (PQS 28903). The inverted conformation stimulates the formation of a hairpin-like structure (see Figure ).

11.

11

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Spatial structure SARS-CoV-2 RNA segments 28903–28939 with Q4 PQS 28903 and without and with pseudouridine at position 28927 after 250 ns molecular dynamics.

Conclusions

The phylogenetic analysis of approximately 100,000 SARS-CoV-2 genomes from various countries over a five-year period has revealed that mutations that disrupt quadruplex 28903 are intolerant, indicating the functional importance of this quadruplex. It has been shown that the analogue of G4 28903 in the SARS-CoV genome is located in a similar mRNA domain, which also supports the significance of this G4. Besides, we showed that the triple mutation in the domain containing G4 28903 has become dominant in recent years. It results in the alteration of its location and increased the probability of its formation.

According to the literature, PQS 28903 is capable of forming a wide variety of structures (hairpin, unimolecular G4, dimeric G4, tetrameric G4, and G-triplex). Currently, the role of these structures in the viral life cycle remains unclear. In this work, we studied the formation of hairpin and unimolecular G4 structures. Based on the structure of the potential quadruplex at position 28903 of SARS-CoV-2 genomic RNA, two- and its three-dimensional geometrical structures were studied as well as the energetical and dynamical properties of four G-quadruplexes and three hairpins. Analyzing quadruplex geometry, it was found that there is an unusual type of hydrogen bonding that stabilizes the geometry of G-quadruplexes, and it is called Watson–Crick-like hydrogen bonding. Formation of such hydrogen bonds is accompanied by replacing traditional Hoogsteen connections and keeping the geometry of the G-quadruplex. However, Watson–Crick-like hydrogen bonds accumulate much less energy compared with Hoogsteen ones. This fact makes Q2 dynamically unstable. In contrast, G-quadruplexes, which utilize the traditional Hoogsteen type of hydrogen bonding, demonstrate a quite stable behavior, as well as hairpins, which can be formed concurrently by the same SARS-CoV-2 sequence that forms G-quadruplex.

The obtained data testify about the time stability of both quadruplex and hairpin conformation of PQS 28903, which can mean their independent folding pathways and coexistence in the ratio, which does not depend on energy barrier but on features of cellular/environment conditions (for example, ion amount and composition, as described in the literature).

We also consider the impact of pseudouridine, which is colocalized with dynamically stable G-quadruplexes or presents in hairpins on their dynamic behavior. It was found that the presence of pseudouridine leads to an increase in the free energy of both dynamically stable (Q3 and Q4) quadruplexes and also increases the corresponding values of the standard deviation, which in the case of Q4 leads to de stabilization of the G4-quadruplex over time, namely, due to unwinding. Conversely, pseudouridine partially stabilizes the structure of the H1 hairpin, reducing the free energy of PQS 28903 in this conformation.

Supplementary Material

ao5c02568_si_001.pdf (430.3KB, pdf)

Acknowledgments

This work used resources of the Center for Computationally Assisted Science and Technology (CCAST) at North Dakota State University, which were made possible in part by NSF MRI Award No. 2019077. Supercomputing support from CCAST HPC System at NDSU and Wroclaw Center for Networking and Super Computing is greatly acknowledged.

MD trajectories and quantum-chemically optimized Cartesian coordinates for all considered in the publication structures can be found in Zenodo EU open repository. The following is https://zenodo.org/records/14253828?preview = 1&token = eyJhbGciOiJIUzUxMiJ9.eyJpZCI6Ijc2NjhiOGU3LTI1NjktNDdmNC04N2I1LTEwM2QxYTc5NTMxYSIsImRhdGEiOnt9LCJyYW5kb20iOiIxMjMzMWI1MDAxYmVmNTM1M2VhNmQyY2NlNzEyYmUzZiJ9.yoxAuArCi236DwQqSdToMBqSrNAEfo0_W3jRucHpof3ApeiqeOI4Rd26jc7eMfOjwsvdms0IREcRYvy9tmGgbw is the temporary link to reach those materials. The https://doi.org/10.5281/zenodo.14253828 is the WEB address of the link in case the manuscript is accepted.

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.5c02568.

  • Additional computational details extending the information presented in the article (PDF)

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. The authors contributed equally.

The study was funded by the National Research Foundation of Ukraine, Project # 2021.01/0087.

The authors declare no competing financial interest.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

ao5c02568_si_001.pdf (430.3KB, pdf)

Data Availability Statement

MD trajectories and quantum-chemically optimized Cartesian coordinates for all considered in the publication structures can be found in Zenodo EU open repository. The following is https://zenodo.org/records/14253828?preview = 1&token = eyJhbGciOiJIUzUxMiJ9.eyJpZCI6Ijc2NjhiOGU3LTI1NjktNDdmNC04N2I1LTEwM2QxYTc5NTMxYSIsImRhdGEiOnt9LCJyYW5kb20iOiIxMjMzMWI1MDAxYmVmNTM1M2VhNmQyY2NlNzEyYmUzZiJ9.yoxAuArCi236DwQqSdToMBqSrNAEfo0_W3jRucHpof3ApeiqeOI4Rd26jc7eMfOjwsvdms0IREcRYvy9tmGgbw is the temporary link to reach those materials. The https://doi.org/10.5281/zenodo.14253828 is the WEB address of the link in case the manuscript is accepted.

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