Conformational Ensembles of Noncoding Elements in the SARS-CoV-2 Genome from Molecular Dynamics Simulations

The 5'-terminal stem-loop RNA element of SARS-CoV-2 features highly dynamic structural elements that are sensitive to differences in cellular pH

We present the nuclear magnetic resonance spectroscopy (NMR) solution structure of the 5'-terminal stem loop 5_SL1 (SL1) of the SARS-CoV-2 genome. SL1 contains two A-form helical elements and two regions with non-canonical structure, namely an apical pyrimidine-rich loop and an asymmetric internal loop with one and two nucleotides at the 5'- and 3'-terminal part of the sequence, respectively. The conformational ensemble representing the averaged solution structure of SL1 was validated using NMR residual dipolar coupling (RDC) and small-angle X-ray scattering (SAXS) data. We show that the internal loop is the major binding site for fragments of low molecular weight. This internal loop of SL1 can be stabilized by an A12-C28 interaction that promotes the transient formation of an A+•C base pair. As a consequence, the pKa of the internal loop adenosine A12 is shifted to 5.8, compared to a pKa of 3.63 of free adenosine. Furthermore, applying a recently developed pH-differential mutational profiling (PD-MaP) approach, we not only recapitulated our NMR findings of SL1 but also unveiled multiple sites potentially sensitive to pH across the 5'-UTR of SARS-CoV-2.

Hierarchical Assembly of Single-Stranded RNA

Single-stranded RNA (ssRNA) plays a major role in the flow of genetic information-most notably, in the form of messenger RNA (mRNA)-and in the regulation of biological processes. The highly dynamic nature of chains of unpaired nucleobases challenges structural characterizations of ssRNA by experiments or molecular dynamics (MD) simulations alike. Here, we use hierarchical chain growth (HCG) to construct ensembles of ssRNA chains. HCG assembles the structures of protein and nucleic acid chains from fragment libraries created by MD simulations. Applied to homo- and heteropolymeric ssRNAs of different lengths, we find that HCG produces structural ensembles that overall are in good agreement with diverse experiments, including nuclear magnetic resonance (NMR), small-angle X-ray scattering (SAXS), and single-molecule Förster resonance energy transfer (FRET). The agreement can be further improved by ensemble refinement using Bayesian inference of ensembles (BioEn). HCG can also be used to assemble RNA structures that combine base-paired and base-unpaired regions, as illustrated for the 5' untranslated region (UTR) of SARS-CoV-2 RNA.

Enhanced molecular dynamic simulation studies unravel long-range effects caused by sequence variations and partner binding in RNA aptamers

Intrinsic flexibility and structural modularity are two common features of RNA molecules. Although functionally crucial, RNA plasticity often represents a major complication in high-resolution structural studies. To overcome this problem, RNAs may be rigidified through the complexation with high-affinity partners such as Fab molecules. This approach has been previously used to characterize the DIR2-aptamer. However, possible perturbations induced by the insertion of the Fab binding site on the DIR2-aptamer conformational properties were not investigated. Here, using enhanced molecular dynamics simulations, we compared the dynamics of the DIR2 aptamer holding the Fab binding site with that of the parental sequence. Our results suggest that the L2-loop modification for the Fab recognition leads to a significant increase in local flexibility that also affects the mobility of distant regions. The trajectories provide clear indications of the groups and the interactions mediating the dynamics transfer in DIR2. The effectiveness of our approach in addressing RNA flexibility was further corroborated by showing its ability to reproduce the most important events affecting the NF-κB RNA aptamer upon dissociation from the partner. Therefore, REMD analyses, a rarely adopted technique to unravel the structural/dynamical properties of aptamers, could efficiently complement experimental data guiding the rational design of nucleic acid therapeutics.

High-resolution structure of stem-loop 4 from the 5'-UTR of SARS-CoV-2 solved by solution state NMR

We present the high-resolution structure of stem-loop 4 of the 5'-untranslated region (5_SL4) of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) genome solved by solution state nuclear magnetic resonance spectroscopy. 5_SL4 adopts an extended rod-like structure with a single flexible looped-out nucleotide and two mixed tandem mismatches, each composed of a G•U wobble base pair and a pyrimidine•pyrimidine mismatch, which are incorporated into the stem-loop structure. Both the tandem mismatches and the looped-out residue destabilize the stem-loop structure locally. Their distribution along the 5_SL4 stem-loop suggests a role of these non-canonical elements in retaining functionally important structural plasticity in particular with regard to the accessibility of the start codon of an upstream open reading frame located in the RNA's apical loop. The apical loop-although mostly flexible-harbors residual structural features suggesting an additional role in molecular recognition processes. 5_SL4 is highly conserved among the different variants of SARS-CoV-2 and can be targeted by small molecule ligands, which it binds with intermediate affinity in the vicinity of the non-canonical elements within the stem-loop structure.

SARS-CoV-2 external structures interacting with nanospheres using docking and molecular dynamics

Coronavirus is caused by the SARS-CoV-2 virus has shown rapid proliferation and scarcity of treatments with proven effectiveness. In this way, we simulated the hospitalization of carbon nanospheres, with external active sites of the SARS-CoV-2 virus (M-Pro, S-Gly and E-Pro), which can be adsorbed or inactivated when interacting with the nanospheres. The computational procedures performed in this work were developed with the SwissDock server for molecular docking and the GROMACS software for molecular dynamics, making it possible to extract relevant data on affinity energy, distance between molecules, free Gibbs energy and mean square deviation of atomic positions, surface area accessible to solvents. Molecular docking indicates that all ligands have an affinity for the receptor's active sites. The nanospheres interact favorably with all proteins, showing promising results, especially C60, which presented the best affinity energy and RMSD values ​​for all protein macromolecules investigated. The C60 with E-Pro exhibited the highest affinity energy of -9.361 kcal/mol, demonstrating stability in both molecular docking and molecular dynamics simulations. Our RMSD calculations indicated that the nanospheres remained predominantly stable, fluctuating within a range of 2 to 3 Å. Additionally, the analysis of other structures yielded promising results that hold potential for application in other proteases.Communicated by Ramaswamy H. Sarma.

Interactions between carbon nanotubes and external structures of SARS-CoV-2 using molecular docking and molecular dynamics

Molecular modeling techniques are used to describe the process of interaction between nanotubes and the main structures of the Covid-19 virus: the envelope protein, the main protease, and the Spike glycoprotein. Molecular docking studies show that the ligands have interaction characteristics capable of adsorbing the structures. Molecular dynamics simulations provide information on the mean squared deviation of atomic positions ​​between 0.5 and 3.0 Å. The Gibbs free energy model and solvent accessible surface area approaches are used. Through the results obtained through molecular dynamics simulations, it is noted that the zig-zag nanotube prefers to interact with E-pro, M-pro, and S-gly, respectively. Molecular couplings and free energy showed that the S-gly active site residues strongly interact with zigzag, chiral, and armchair nanotubes, in this order. The interactions demonstrated in this manuscript may predict some promising candidates for virus antagonists, which may be confirmed through experimental approaches.

RNA folding pathways from all-atom simulations with a variationally improved history-dependent bias

Atomically detailed simulations of RNA folding have proven very challenging in view of the difficulties of developing realistic force fields and the intrinsic computational complexity of sampling rare conformational transitions. As a step forward in tackling these issues, we extend to RNA an enhanced path-sampling method previously successfully applied to proteins. In this scheme, the information about the RNA's native structure is harnessed by a soft history-dependent biasing force promoting the generation of productive folding trajectories in an all-atom force field with explicit solvent. A rigorous variational principle is then applied to minimize the effect of the bias. Here, we report on an application of this method to RNA molecules from 20 to 47 nucleotides long and increasing topological complexity. By comparison with analog simulations performed on small proteins with similar size and architecture, we show that the RNA folding landscape is significantly more frustrated, even for relatively small chains with a simple topology. The predicted RNA folding mechanisms are found to be consistent with the available experiments and some of the existing coarse-grained models. Due to its computational performance, this scheme provides a promising platform to efficiently gather atomistic RNA folding trajectories, thus retain the information about the chemical composition of the sequence.

Mutagenesis and structural studies reveal the basis for the specific binding of SARS-CoV-2 SL3 RNA element with human TIA1 protein

Viral RNA-host protein interactions are indispensable during RNA virus transcription and replication, but their detailed structural and dynamical features remain largely elusive. Here, we characterize the binding interface for the SARS-CoV-2 stem-loop 3 (SL3) cis-acting element to human TIA1 protein with a combined theoretical and experimental approaches. The highly structured SARS-CoV-2 SL3 has a high binding affinity to TIA1 protein, in which the aromatic stacking, hydrogen bonds, and hydrophobic interactions collectively direct this specific binding. Further mutagenesis studies validate our proposed 3D binding model and reveal two SL3 variants have enhanced binding affinities to TIA1. And disruptions of the identified RNA-protein interactions with designed antisense oligonucleotides dramatically reduce SARS-CoV-2 infection in cells. Finally, TIA1 protein could interact with conserved SL3 RNA elements within other betacoronavirus lineages. These findings open an avenue to explore the viral RNA-host protein interactions and provide a pioneering structural basis for RNA-targeting antiviral drug design.

Integrating experimental data with molecular simulations to investigate RNA structural dynamics

Conformational dynamics is crucial for ribonucleic acid (RNA) function. Techniques such as nuclear magnetic resonance, cryo-electron microscopy, small- and wide-angle X-ray scattering, chemical probing, single-molecule Förster resonance energy transfer, or even thermal or mechanical denaturation experiments probe RNA dynamics at different time and space resolutions. Their combination with accurate atomistic molecular dynamics (MD) simulations paves the way for quantitative and detailed studies of RNA dynamics. First, experiments provide a quantitative validation tool for MD simulations. Second, available data can be used to refine simulated structural ensembles to match experiments. Finally, comparison with experiments allows for improving MD force fields that are transferable to new systems for which data is not available. Here we review the recent literature and provide our perspective on this field.

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

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

Insights into the structural stability of major groove RNA triplexes by WAXS-guided MD simulations

RNA triple helices are commonly observed tertiary motifs that are associated with critical biological functions, including signal transduction. Because the recognition of their biological importance is relatively recent, their full range of structural properties has not yet been elucidated. The integration of solution wide-angle X-ray scattering (WAXS) with molecular dynamics (MD) simulations, described here, provides a new way to capture the structures of major-groove RNA triplexes that evade crystallographic characterization. This method yields excellent agreement between measured and computed WAXS profiles and allows for an atomically detailed visualization of these motifs. Using correlation maps, the relationship between well-defined features in the scattering profiles and real space characteristics of RNA molecules is defined, including the subtle conformational variations in the double-stranded RNA upon the incorporation of a third strand by base triples. This readily applicable approach has the potential to provide insight into interactions that stabilize RNA tertiary structure that enables function.

Structure of the 5' untranslated region in SARS-CoV-2 genome and its specific recognition by innate immune system via the human oligoadenylate synthase 1

2'-5'-Oligoadenylate synthetase 1 (OAS1) is one of the key enzymes driving the innate immune system response to SARS-CoV-2 infection whose activity has been related to COVID-19 severity. OAS1 is a sensor of endogenous RNA that triggers the 2'-5'-oligoadenylate/RNase L pathway. Upon SARS-CoV-2 infection, OAS1 is responsible for the recognition of viral RNA and has been shown to possess a particularly high sensitivity for the 5'-untranslated (5'-UTR) RNA region, which is organized in a double-strand stem loop motif (SL1). Here we report the structure of the SL1/OAS1 complex also rationalizing the high affinity for OAS1.

Extended ensemble simulations of a SARS-CoV-2 nsp1-5'-UTR complex

Nonstructural protein 1 (nsp1) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a 180-residue protein that blocks translation of host mRNAs in SARS-CoV-2-infected cells. Although it is known that SARS-CoV-2’s own RNA evades nsp1’s host translation shutoff, the molecular mechanism underlying the evasion was poorly understood. We performed an extended ensemble molecular dynamics simulation to investigate the mechanism of the viral RNA evasion. Simulation results suggested that the stem loop structure of the SARS-CoV-2 RNA 5’-untranslated region (SL1) binds to both nsp1’s N-terminal globular region and intrinsically disordered region. The consistency of the results was assessed by modeling nsp1-40S ribosome structure based on reported nsp1 experiments, including the X-ray crystallographic structure analysis, the cryo-EM electron density map, and cross-linking experiments. The SL1 binding region predicted from the simulation was open to the solvent, yet the ribosome could interact with SL1. Cluster analysis of the binding mode and detailed analysis of the binding poses suggest residues Arg124, Lys47, Arg43, and Asn126 may be involved in the SL1 recognition mechanism, consistent with the existing mutational analysis.

The pandemic of COVID-19 is still rampant all over the world as of 2021 June. SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), the causative pathogen of COVID-19, encodes a protein called nsp1 (nonstructural protein 1), which modulates and hijacks the ribosome of the infected host cells. With nsp1, infected human cells selectively translate SARS-CoV-2’s RNA, which increases the virus reproduction efficiency while evading the host immunity. Though it has been known that nsp1 recognizes characteristic stem-loop structure at 5’-end of SARS-CoV-2’s RNA (called SL1), the molecular mechanism underlying the recognition has been poorly understood. We investigated the mechanism of selective translation using the all-atom molecular dynamics simulation of nsp1-SL1 complex. Our simulation results suggest that the binding between nsp1 and SL1 is multi-modal. The results also imply that both the N-terminal globular part and the C-terminal flexible tail of nsp1 are involved in the binding. The residues involved in nsp1-SL1 binding coincides with the known mutant analyses of SARS-CoV-1 and SARS-CoV-2, as well as experimental evidence about nsp1-ribosome interactions.