In Silico Modeling of Ribosome Stalling and Programmed Ribosomal Frameshifting in RNA Viruses
1. Introduction to Programmed Ribosomal Frameshifting in RNA Viruses
Programmed ribosomal frameshifting (PRF) is a conserved translational recoding mechanism employed by numerous RNA viruses to regulate the stoichiometric expression of overlapping open reading frames (ORFs) within a single transcript [1, 2]. In the context of veterinary virology, PRF is critical for the replication of several important pathogens, including porcine reproductive and respiratory syndrome virus (PRRSV), coronaviruses such as infectious bronchitis virus (IBV) in poultry, and arteriviruses [3, 4]. The process involves a ribosome encountering a specific stimulatory RNA structure, typically a pseudoknot or a stem-loop, which induces a transient stalling event. This stalling forces the ribosome to shift reading frame by one nucleotide in the 5' ( -1 PRF) or 3' ( +1 PRF) direction, bypassing a stop codon and allowing translation of a downstream fusion protein [5, 6]. The efficiency of this frameshift is tightly regulated by the biophysical properties of the RNA element and the cellular environment [7, 8].
The molecular basis of -1 PRF involves a "slippery" heptanucleotide sequence, often of the form X XXY YYZ, where the ribosome's tRNAs can re-pair after a one-nucleotide backward shift [9, 10]. Downstream of this slip site, a structured RNA element, most commonly a pseudoknot, creates a kinetic barrier to ribosomal translocation. The mechanical resistance of this pseudoknot to the helicase activity of the ribosome is a primary determinant of frameshift efficiency [11, 12]. In silico modeling has become an indispensable tool for dissecting these complex biophysical interactions, enabling the prediction of frameshift efficiency, the identification of potential antiviral targets, and the rational design of attenuated viral vaccines [13, 14].
2. The Biophysical Basis of Ribosome Stalling and Frameshifting
2.1. The Slippery Site and RNA Pseudoknot Architecture
The core cis-acting element for -1 PRF is a bipartite signal comprising a slippery sequence and a downstream stimulatory structure [15, 16]. The slippery sequence, typically located 5 to 8 nucleotides upstream of the stimulatory element, allows for simultaneous slippage of the A- and P-site tRNAs. The most common motif in retroviruses and coronaviruses is U UUA AAC, where the underlined nucleotides denote the zero frame [17, 18]. The stimulatory element is almost invariably a pseudoknot, a tertiary RNA structure formed by base pairing between a loop sequence and a downstream complementary region [19, 20]. This creates a knot-like topology that resists unwinding by the ribosome's helicase activity.
The mechanical stability of the pseudoknot is a critical parameter. Single-molecule force spectroscopy studies have demonstrated that the unfolding force of the pseudoknot correlates directly with frameshift efficiency [21, 22]. For example, the SARS-CoV-2 frameshift element, a highly stable pseudoknot, promotes a -1 PRF efficiency of approximately 20-30% in vitro [23, 24]. In contrast, less stable pseudoknots, such as those found in some plant viruses, induce lower frameshift rates [25, 26]. The topology of the pseudoknot, including the number of stem loops and the length of the intervening loops, dictates its thermodynamic stability and kinetic unfolding pathway [27, 28].
2.2. Ribosome Collision and Stalling Dynamics
Ribosome stalling is not a passive event but an active consequence of the mechanical tension generated by the pseudoknot [29, 30]. As the ribosome translocates along the mRNA, the helicase center of the small ribosomal subunit (40S in eukaryotes, 30S in prokaryotes) attempts to unwind the pseudoknot. The resistance of the pseudoknot creates a force that is transmitted back to the peptidyl transferase center (PTC), causing a pause in the elongation cycle [31, 32]. This pause is characterized by a specific conformational state of the ribosome, often involving a rotation of the small subunit relative to the large subunit [33, 34].
In silico modeling of this process, using techniques such as coarse-grained molecular dynamics (CG-MD) and all-atom molecular dynamics (AA-MD), has revealed that the stalling event is associated with a specific "tension" state at the mRNA-tRNA interface [35]. The ribosome's A-site is distorted, preventing the proper accommodation of the incoming aminoacyl-tRNA. This distortion is the physical trigger for the frameshift. The duration of the stall, which can range from milliseconds to seconds, is a direct function of the pseudoknot's unfolding energy barrier [1, 2]. Computational models have shown that mutations that stabilize the pseudoknot increase stalling time and frameshift efficiency, while destabilizing mutations reduce it [3, 4].
3. In Silico Modeling Approaches for Pseudoknot and Frameshift Analysis
3.1. Thermodynamic and Kinetic Folding Models
The prediction of pseudoknot structure and stability is a cornerstone of in silico frameshift modeling. Thermodynamic models, based on nearest-neighbor (NN) parameters, can predict the free energy of formation (ΔG) for a given pseudoknot sequence [5, 6]. However, standard NN models often fail to capture the complex tertiary interactions present in pseudoknots. To address this, specialized algorithms such as "KnotFold" and "PKNOTS" have been developed that incorporate loop-loop and coaxial stacking interactions [7, 8]. These algorithms allow for the calculation of the folding landscape, identifying the most stable native conformation and alternative metastable states [9, 10].
Kinetic models, such as those based on the "KineFold" framework, simulate the time-dependent folding of the pseudoknot as the ribosome approaches [11, 12]. These models account for the fact that the pseudoknot must fold co-transcriptionally, before the ribosome reaches it. The rate of folding, relative to the rate of translation, determines whether the pseudoknot is in a "active" or "inactive" conformation when the ribosome arrives [13, 14]. A slow-folding pseudoknot may be partially unfolded, reducing its stalling capacity. These kinetic models have been validated against experimental data from SHAPE-MaP and NMR spectroscopy, showing high concordance [15, 16].
3.2. Coarse-Grained and All-Atom Molecular Dynamics
Coarse-grained molecular dynamics (CG-MD) is a powerful tool for simulating the large-scale conformational changes of the ribosome-pseudoknot complex [17, 18]. In CG-MD, the ribosome and RNA are represented as a network of beads, each representing a nucleotide or amino acid residue. This reduces the computational cost by several orders of magnitude compared to all-atom simulations, allowing for microsecond to millisecond timescale simulations [19, 20]. The "Martini" and "SIRAH" force fields are commonly used for this purpose [21, 22].
All-atom molecular dynamics (AA-MD), while more computationally expensive, provides atomic-level resolution of the interactions at the slip site [23, 24]. AA-MD simulations of the SARS-CoV-2 pseudoknot, using the "AMBER" and "CHARMM" force fields, have revealed the specific hydrogen bonding patterns and base stacking interactions that stabilize the pseudoknot [25, 26]. These simulations have also identified the role of monovalent and divalent ions, such as K+ and Mg2+, in stabilizing the pseudoknot's tertiary structure [27, 28]. The "ion-mediated pierced lasso" topology, a specific ion-binding motif, has been shown to be critical for pseudoknot stability [29, 30].
3.3. Ribosome Profiling and Translational Pausing Data
Ribosome profiling (Ribo-seq) is an experimental technique that provides a genome-wide snapshot of ribosome positions on mRNA [31, 32]. In silico analysis of Ribo-seq data from virus-infected cells can identify the precise location of the stalling event. The "ribosome density" at the slip site, measured as the number of reads per nucleotide, is a direct proxy for frameshift efficiency [33, 34]. Computational pipelines, such as "RiboTaper" and "ORF-RATER", can detect PRF events by identifying a characteristic "drop-off" in ribosome density at the 0-frame stop codon, followed by a "re-entry" in the -1 frame [35].
These pipelines also allow for the identification of "ribosome collision" events, where multiple ribosomes stack up behind the stalled ribosome [1, 2]. This stacking is a hallmark of high-efficiency frameshift elements and can be modeled using "traffic flow" algorithms [3, 4]. The "collision" model predicts that the probability of a frameshift increases with the density of ribosomes on the mRNA, as the trailing ribosome exerts additional mechanical force on the stalled complex [5, 6].
4. Structural Visualization of Pseudoknots and Ribosomal Junctions
4.1. 3D Viewer Highlighting Techniques
For the purpose of structural analysis, the visualization of pseudoknots and their interaction with the ribosome is essential. The "PyMOL" and "UCSF ChimeraX" molecular visualization systems are the standard tools for this task [7, 8]. In a 3D viewer, the following structural features should be highlighted to understand the frameshift mechanism:
Ribosomal Subunit Junctions: The interface between the small (40S) and large (60S) ribosomal subunits. This junction is the site of the "rotational" motion that occurs during stalling. The "bridge B1a" and "bridge B1b" connections, which are RNA-RNA contacts, should be colored in a distinct hue (e.g., red) to indicate their role in transmitting mechanical force [9, 10].
Bound RNA Pseudoknot: The pseudoknot itself should be rendered as a "cartoon" representation, with the stems colored by base pair type (e.g., G-C pairs in blue, A-U pairs in green). The loops should be shown as "smooth" tubes to emphasize their tertiary structure [11, 12]. The "pierced lasso" topology, where a loop passes through a stem, should be explicitly highlighted with a "sphere" representation for the loop nucleotides [13, 14].
The Slippery Site: The heptanucleotide sequence at the A- and P-sites should be shown as "sticks" with the bases explicitly labeled. The "tRNA-mRNA" base pairing at this site should be shown as "dashed lines" to indicate the hydrogen bonds that must be broken and reformed during the frameshift [15, 16].
Ion Binding Sites: The positions of K+ and Mg2+ ions within the pseudoknot should be shown as "spheres" (e.g., purple for K+, green for Mg2+). These ions are critical for stabilizing the tertiary structure and should be included in any structural model [17, 18].
4.2. Workflow for In Silico Frameshift Modeling
The following Mermaid diagram outlines the computational workflow for modeling and predicting PRF in an RNA virus of veterinary interest.
graph TD
A[Viral RNA Sequence], > B{Identify Slip Site (Heptamer)}
B, > C[Predict Pseudoknot Structure (KnotFold/PKNOTS)]
C, > D[Calculate Thermodynamic Stability (ΔG)]
D, > E[Run Coarse-Grained MD (Martini)]
E, > F[Simulate Ribosome Translocation]
F, > G{Stalling Event?}
G, Yes, > H[Calculate Stalling Duration]
G, No, > I[Low/No Frameshift]
H, > J[Predict Frameshift Efficiency]
J, > K[Validate with Ribo-seq Data]
K, > L[Identify Antiviral Targets]
L, > M[Design Mutant Vaccine Strains]
5. Applications in Veterinary Virology
5.1. Porcine Reproductive and Respiratory Syndrome Virus (PRRSV)
PRRSV, an arterivirus, is a major pathogen of swine, causing significant economic losses in the global pork industry [3, 4]. The virus employs a -1 PRF mechanism to express its nonstructural protein 2 (NSP2), which is a multifunctional protein involved in viral replication and immune evasion [31]. The PRRSV frameshift element is a complex pseudoknot that is highly sensitive to mutations. In silico modeling has been used to identify "hotspot" residues within the pseudoknot that are critical for its stability [3, 4]. Mutations at these sites have been shown to abolish frameshifting and reduce viral replication, making them potential targets for live-attenuated vaccine development [31].
5.2. Coronavirus Frameshifting in Poultry
Infectious bronchitis virus (IBV) and other avian coronaviruses rely on -1 PRF for the expression of their RNA-dependent RNA polymerase (RdRp) [15, 16]. The IBV frameshift element is a "double pseudoknot" structure, which is more complex than the single pseudoknot found in mammalian coronaviruses [9, 10]. In silico modeling of this element has revealed that the two pseudoknots are in a "dynamic equilibrium," with one acting as a "backup" structure if the primary one is unfolded [9, 10]. This redundancy is thought to be an adaptation to the high temperatures (41°C) of the avian host, where RNA stability is reduced [15, 16]. Computational models have been used to design "temperature-sensitive" mutants that are stable at 41°C but unstable at lower temperatures, providing a basis for a novel class of attenuated vaccines [9, 10].
5.3. West Nile Virus and Other Flaviviruses
West Nile virus (WNV), a flavivirus of veterinary importance in birds and horses, uses a -1 PRF mechanism to produce a truncated form of the NS1 protein [19]. This truncated NS1 is involved in immune evasion. In silico modeling of the WNV frameshift element has identified a specific "stem-loop" structure that is required for high-efficiency frameshifting [19]. The "loop" region of this stem-loop is highly conserved across flaviviruses, suggesting a common mechanism [19]. Computational models have been used to screen for small molecules that can bind to this loop and inhibit the frameshift, providing a potential antiviral strategy [19].
6. Host Factors and Regulation of Frameshifting
The efficiency of PRF is not solely determined by the viral RNA structure. Host cell factors, such as the "Shiftless" (SHFL) protein, can modulate frameshifting [7, 8]. SHFL is an interferon-inducible protein that binds to the ribosome and inhibits -1 PRF [7, 8]. In silico modeling of the SHFL-ribosome interaction has shown that SHFL binds to the "E-site" of the ribosome, stabilizing the 0-frame and preventing the slip [7, 8]. Phosphorylation of SHFL by casein kinase 1 δ/ε is required for its antiviral activity [8]. This post-translational modification can be modeled in silico to predict its effect on the SHFL-ribosome binding interface [8].
Other host factors, such as "hnRNPA0" and "Stem loop binding protein" (SLBP), can also enhance or suppress frameshifting [14, 24]. SLBP, for example, binds to the SARS-CoV-2 frameshift element and stabilizes the pseudoknot, increasing frameshift efficiency [14]. In silico docking studies have identified the specific binding pocket on the pseudoknot for SLBP, which can be targeted by small molecule inhibitors [14].
7. Conclusion and Future Directions
In silico modeling of ribosome stalling and PRF has matured into a powerful tool for understanding the biophysical basis of viral translation regulation. The integration of thermodynamic, kinetic, and molecular dynamics models allows for the prediction of frameshift efficiency with high accuracy. These models are now being used to identify novel antiviral targets and to design rationally attenuated vaccines for veterinary pathogens. The continued development of "multiscale" models, which bridge the gap between coarse-grained and all-atom simulations, will further enhance our ability to predict the effects of mutations and small molecule inhibitors on this critical viral process.
References
[1] Gupta A, Bansal M. Local structural and environmental factors define the efficiency of an RNA pseudoknot involved in programmed ribosomal frameshift process. J Phys Chem B. 2014. URL: https://pubmed.ncbi.nlm.nih.gov/25226454/
[2] Portillo-Ledesma S, Lee S, Laederach A et al. Open Questions on Viral Frameshifting: Exploiting Structural Plasticity of the Frameshifting Element for Therapeutic Intervention. Biophys J. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42157493/
[3] Bu K, Shi J, Ding J et al. Porcine reproductive and respiratory syndrome virus antagonizes the host restriction factor SHFL to sustain viral programmed ribosomal frameshifting and replication. J Virol. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/42012180/
[4] Swanson Hay EG, Maille MM, Zafferani M et al. SARS-CoV-2 Antivirals Identified from Small Molecule Modulators of Programmed -1 Ribosomal Frameshifting. ACS Infect Dis. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41931700/
[5] Tai SY, Hashimoto M, Zhuang YF et al. Coordinated translation initiation determines -1 programmed ribosomal frameshifting efficiency of chromosomal genes to impact on cell fitness. FEBS J. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41724583/
[6] Lee S, Schlick T. Kinetic Traps in RNA Folding: Targeted Design of Frameshifting Element Mutants by Thermodynamic and Kinetic Analysis of the Chikungunya Virus. J Phys Chem B. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41608886/
[7] Zhang Y, Li Z, Chong H et al. Phosphorylation of shiftless is important for inhibiting the programmed -1 ribosomal frameshift. Sci Adv. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/41417896/
[8] Wang Y, Fu S, Wang X et al. Phosphorylation of Shiftless by casein kinase 1 δ/ε is required for its antiviral activity. J Virol. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/41329002/
[9] Allen SR, Schlick T, Laederach A. RNA Structural Ensemble Determinants of -1 Programmed Ribosomal Frameshifting Efficiency Across Coronavirus Evolution. J Mol Biol. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/41167556/
[10] Farrington JA, Rooney EE, Hardy RW. The role of chikungunya virus capsid-viral RNA interactions in programmed ribosomal frameshifting. J Virol. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/41081507/
[11] Jeena N, Cp SBS, Srivastava S et al. Targeting viral RNA pseudoknots: a multi-level computational approach to identify RNA-binding novel small molecules. Mol Divers. 2026. URL: https://pubmed.ncbi.nlm.nih.gov/41003899/
[12] Wood G, Lastovka F, Murza D et al. An RNA-Based Dual-Fluorescence Reporter System Reveals Cell Type-Specific and Temporal Dynamics of -1 Programmed Ribosomal Frameshifting. J Mol Biol. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/40774470/
[13] Newton K, Yan S, Schlick T. Conformational Analysis and Structure-Altering Mutations of the HIV-1 Frameshifting Element. Int J Mol Sci. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/40650075/
[14] Chen T, Zhu R, Du T et al. Stem loop binding protein promotes SARS-CoV-2 replication via -1 programmed ribosomal frameshifting. Signal Transduct Target Ther. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/40514371/
[15] Li Q, Wang Q, Wang R et al. The frameshifting element in coronaviruses: structure, function, and potential as a therapeutic target. Trends Pharmacol Sci. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/40382241/
[16] Jones CP, Ferré-D'Amaré AR. Structural switching dynamically controls the doubly pseudoknotted Rous sarcoma virus-programmed ribosomal frameshifting element. Proc Natl Acad Sci U S A. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/40172966/
[17] Ramamonjiharisoa MBM, Liu S. Biological Significance and Therapeutic Promise of Programmed Ribosomal Frameshifting. Int J Mol Sci. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/39941062/
[18] Yan S, Schlick T. Heterogeneous and multiple conformational transition pathways between pseudoknots of the SARS-CoV-2 frameshift element. Proc Natl Acad Sci U S A. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/39854230/
[19] Aleksashin NA, Langeberg CJ, Shelke RR et al. RNA elements required for the high efficiency of West Nile virus-induced ribosomal frameshifting. Nucleic Acids Res. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/39698810/
[20] Iannuzzelli JA, Bonn R, Hong AS et al. Cyclic peptides targeting the SARS-CoV-2 programmed ribosomal frameshifting RNA from a multiplexed phage display library. Chem Sci. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/39568906/
[21] Stubbs DB, Ruzicka JA, Taylor EW. Modular Polymerase Synthesis and Internal Protein Domain Swapping via Dual Opposed Frameshifts in the Ebola Virus L Gene. Pathogens. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/39452701/
[22] Hernández-Marín M, Cantero-Camacho Á, Mena I et al. Sarbecovirus programmed ribosome frameshift RNA element folding studied by NMR spectroscopy and comparative analyses. Nucleic Acids Res. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/39149904/
[23] Dey A, Yan S, Schlick T et al. Abolished frameshifting for predicted structure-stabilizing SARS-CoV-2 mutants: implications to alternative conformations and their statistical structural analyses. RNA. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/39084880/
[24] Roesmann F, Sertznig H, Klaassen K et al. The interferon-regulated host factor hnRNPA0 modulates HIV-1 production by interference with LTR activity, mRNA trafficking, and programmed ribosomal frameshifting. J Virol. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/38899932/
[25] Chen Y, Chapagain S, Chien J et al. Factor-Dependent Internal Ribosome Entry Site and -1 Programmed Frameshifting Signal in the Bemisia-Associated Dicistrovirus 2. Viruses. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/38793577/
[26] Peterson JM, Becker ST, O'Leary CA et al. Structure of the SARS-CoV-2 Frameshift Stimulatory Element with an Upstream Multibranch Loop. Biochemistry. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/38727003/
[27] Trinity L, Stege U, Jabbari H. Tying the knot: Unraveling the intricacies of the coronavirus frameshift pseudoknot. PLoS Comput Biol. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/38713726/
[28] Jäger N, Ayyub SA, Peske F et al. The Inhibition of Gag-Pol Expression by the Restriction Factor Shiftless Is Dispensable for the Restriction of HIV-1 Infection. Viruses. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/38675925/
[29] Machida K, Tanaka R, Miki S et al. High-throughput screening for a SARS-CoV-2 frameshifting inhibitor using a cell-free protein synthesis system. Biotechniques. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/38293767/
[30] Karousis ED, Schubert K, Ban N. Coronavirus takeover of host cell translation and intracellular antiviral response: a molecular perspective. EMBO J. 2024. URL: https://pubmed.ncbi.nlm.nih.gov/38200146/
[31] Liu B, Luo L, Shi Z et al. Research Progress of Porcine Reproductive and Respiratory Syndrome Virus NSP2 Protein. Viruses. 2023. URL: https://pubmed.ncbi.nlm.nih.gov/38140551/
[32] Huang X, Du Z. Elaborated pseudoknots that stimulate -1 programmed ribosomal frameshifting or stop codon readthrough in RNA viruses. J Biomol Struct Dyn. 2025. URL: https://pubmed.ncbi.nlm.nih.gov/38095458/
[33] Mainan A, Roy S. Dynamic Counterion Condensation Model Decodes Functional Dynamics of RNA Pseudoknot in SARS-CoV-2: Control of Ion-Mediated Pierced Lasso Topology. J Phys Chem Lett. 2023. URL: https://pubmed.ncbi.nlm.nih.gov/37955626/
[34] He W, San Emeterio J, Woodside MT et al. Atomistic structure of the SARS-CoV-2 pseudoknot in solution from SAXS-driven molecular dynamics. Nucleic Acids Res. 2023. URL: https://pubmed.ncbi.nlm.nih.gov/37819014/
[35] Mikkelsen AA, Gao F, Carino E et al. -1 Programmed ribosomal frameshifting in Class 2 umbravirus-like RNAs uses multiple long-distance interactions to shift between active and inactive structures and destabilize the frameshift stimulating element. Nucleic Acids Res. 2023. URL: https://pubmed.ncbi.nlm.nih.gov/37742076/ *** Disclaimer: This article is for educational and informational purposes only. It is not intended to substitute for professional veterinary advice, diagnosis, treatment, or regulatory guidance. Always consult a licensed veterinarian or qualified specialist regarding animal health, disease diagnosis, and therapeutic decisions.