RNA Folding Research Articles

Investigation on interactions of non-canonical RNAs with proteins.

RNAs are major drivers of phase separation in the formation of biomolecular condensates and can undergo protein-free phase separation in the presence of divalent ions or crowding agents. Much remains to be understood regarding how the complex interplay of base stacking, base pairing, electrostatics, ion interactions, and particularly structural propensities governs RNA phase behavior. Here, we develop an intermediate resolution model for condensates of RNAs (iConRNA) that can capture key local and long-range structural features of dynamic RNAs and simulate their spontaneous phase transitions with Mg2+. Representing each nucleotide using 6 to 7 beads, iConRNA accurately captures base stacking and pairing and includes explicit Mg2+. The model not only reproduces major conformational properties of poly(rA) and poly(rU) but also correctly folds small structured RNAs and predicts their melting temperatures. With an effective model of explicit Mg2+, iConRNA successfully recapitulates experimentally observed lower critical solution temperature phase separation of poly(rA) and triplet repeats, and critically, the nontrivial dependence of phase transitions on RNA sequence, length, concentration, and Mg2+ level. Further mechanistic analysis reveals a key role of RNA folding in modulating phase separation as well as its temperature and ion dependence, besides other driving forces such as Mg2+-phosphate interactions, base stacking, and base pairing. These studies also support iConRNA as a powerful tool for direct simulation of RNA-driven phase transitions, enabling molecular studies of how RNA conformational dynamics and its response to complex condensate environments control the phase behavior and condensate material properties.

Molecular chaperones are machines that consume copious amounts of ATP to facilitate the folding of misfolded proteins or RNA to their functionally competent native states by driving them out of equilibrium. Because the folding landscapes of biomolecules with complex native state topology are rugged, consisting of multiple minima that are separated by large free energy barriers, folding occurs by the kinetic partitioning mechanism according to which only a small fraction of the molecules reach the folded state in biologically viable times. The remaining fraction is kinetically trapped in a manifold of misfolded states. Folding of such recalcitrant proteins and RNA requires chaperones. Although the protein and RNA chaperones are profoundly different in their structure and action, the principles underlying their activity to produce the folded structures can be understood using a unified theoretical framework based on iterative annealing mechanism. Our theory, which quantitatively explains a number of experimental data, shows that both these machines have evolved to maximize the steady-state yield on biological times. Strikingly, the theory predicts that only at a moderate level of RNA chaperone activity is the yield of the self-splicing pre-RNA maximized in vivo.

Here, 18S-rDNA sequences of Blastocystis sp., previously documented from symptomatic (cases) and asymptomatic (controls) carriers, were analyzed to determine their population structure, predict their secondary structure, and examine their interactions with ribosomal proteins (Bud23, RPS5, and RPS18). Phylogenetic and population differentiation analyses were performed using STRUCTURE software V2.3.4. Moreover, an analysis of the rRNA secondary structure and folding of each sequence was performed, and their probability of interaction with ribosomal proteins was determined. Phylogenetic and haplotype analyses sorted the sequences into genetic subtypes ST1, ST2, and ST3, while the population structure showed each cluster as a differentiated subpopulation, suggesting incipient speciation or cryptic species differentiation. Furthermore, the analysis of the secondary structure of rRNA exhibited specific arrangements for each subtype. In addition, the probability of interaction between 18S-rRNA sequences of Blastocystis from cases and controls with RPS5 and RPS18 was significant, matching the biological plausibility of the previously documented finding that control isolates had a lower generation time than isolates obtained from cases. These findings reinforce the hypothesis that ribosomal subtypes ST1–ST3 of Blastocystis represent evolutionarily distinct lineages with the potential to be recognized as future species. Furthermore, they underscore the functional relevance of 18S-rRNA sequences from clinical isolates of Blastocystis.

The SARS-CoV-2 frameshift stimulation element (FSE) is a critical RNA structure that is essential for viral replication and represents a promising target for antiviral intervention. Here, Chemical Cross-Linking and Isolation by Pull-down (Chem-CLIP) covalent target validation and binding site mapping was applied, to identify small-molecule binding pockets within the FSE and ultimately develop a ligandability map. These studies employed ∼ 190 Chem-CLIP fragments, including the fluoroquinolone merafloxacin, previously shown to interact with this element. Covalent mapping defined merafloxacin's binding pocket at a nucleotide-level resolution and revealed interactions that, along with structure-based design, efficient one-pot on-plate synthesis and competitive displacement assays, enabled the development of bioactive compounds with antiviral activity. Complementary chemical probing with dimethyl sulfate (DMS) in the presence of a bioactive ligand, coupled to Deconvolution of RNA Alternative Conformations (DRACO), revealed that compound binding increased the reactivity of specific nucleotides with DMS, indicative of changes in local RNA folding. These results highlight the importance of combining Chem-CLIP and DMS profiling to differentiate direct ligand binding from ligand-induced changes in RNA structure. In addition, in silico pocket analysis of FSE structures derived from cryogenic-electron microscopy (cryo-EM) studies identified four recurring cavities, including the experimentally determined merafloxacin and Chem-CLIP fragments binding pockets. Altogether, the findings advance our understanding of RNA-ligand interactions and support a strategy to design and discover small molecules that bind RNA structures.

In this study, molecular dynamics (MD) simulations are used to investigate the adsorption of a 21‐nucleotide microRNA (miRNA21) to silica surfaces at three pHs, three salt concentrations, and with two salt species. Silica gel has been reported to be an effective biopreservation medium. MD simulations provided molecular‐level details of the adsorption processes that are expected to affect preservation efficacy. Parallel tempering metadynamics in the well‐tempered ensemble enhanced MD sampling and allowed the exploration of adsorbed, desorbed, compact, and extended miRNA21 conformations. Both CHARMM and AMBER force fields are used to explore conformational states. Simulation results indicate that higher salt concentrations correlate to increased binding strength, emphasizing the pivotal role of ion coordination in the adsorption process. Salt‐mediated miRNA–silica interactions are observed, indicating that cations can allow miRNA to approach the silica surface even when the surface is negatively charged. Simulations also revealed that acidic environments significantly weaken the adsorption between miRNA21 and silica surfaces due to fewer salt‐mediated interactions. These findings highlight the influence of environmental factors and salt‐mediated bridging interactions on RNA‐silica adsorption affinity. Simulations suggest that kinetics drive experimentally observed preservation activity. Reweighting of biased trajectories reveal key differences in RNA folding and ion coordination between force fields.

The naphthyridine carbamate dimer (NCD) is a small molecule that recognizes disease-related RNA containing UGGAA repeats associated with spinocerebellar ataxia type 31 (SCA 31) and alleviates the disease phenotype in vitro and in vivo. In this study, we use X-ray crystallography to elucidate the mode of NCD binding in detail. We determine the crystal structures of the RNA–NCD complex and a structure of unliganded RNA. The NCD interacts differently than in previously reported nuclear magnetic resonance structure, forming pseudo-canonical base pairs with guanosine residues located on the same RNA strand. Furthermore, in one of the complexes, the ligand is located between symmetry-related RNA molecules, exhibiting a molecular glue characteristics in crystal lattice formation. The comparison of RNA–NCD and ligand-free models allows the identification of structural changes in RNA upon ligand binding from A-form to Z-RNA-like form. These observations extend our understanding of the interactions between RNA and small compounds and can be useful as a reference model in the development of bioinformatics tools for RNA–ligand structure predictions.

While divalent ions are known to be involved in key biological processes such as RNA folding or DNA-histone interactions, these interactions are poorly captured in molecular dynamics simulations with empirical force fields, which suffer from strong overbinding artifacts. Hence, there is a strong need for improved descriptions of (divalent) ions in nucleic acid simulations. In this work, we explore the possibility to improve ion-binding properties of the popular Amber-OL15 force field using the Electronic Continuum Correction (ECC) approach, which includes electronic polarization through charge scaling, limited here to the phosphate backbone. This strategy yields very promising results, with essentially no degradation of the conformational properties of selected DNA (and a ds-RNA) sequences and a strong improvement of both monovalent ion retention in G-quadruplexes and divalent ion pairing. As the ECC modification appears mostly orthogonal to force field refinements focused on backbone dihedral parameters, this work suggests a systematic way to improve the ion pairing properties of nucleic acids in all-atom MD simulations.

Magnesium ions (Mg2+) play a crucial rolein stabilizingvarious RNA tertiary motifs, such as pseudoknots, G-quadruplexes,kissing loops, and A-minor motifs, to name a few. Despite their importance,the precise location and role of Mg2+ ions in RNA foldingare challenging to characterize both experimentally and computationally.In this study, we employ an all-atom structure-based model integratedwith the dynamic counterion condensation (DCC) model to investigatethe folding and unfolding transitions of apo SAM-II riboswitch RNAat physiological concentrations of Mg2+. Using the EnergyLandscape Visualization Method (ELViM), we trace the transitions betweenconformational phases, focusing on magnesium interactions. ELViM revealskey structural ensembles during the transition from the unfolded tothe folded state, facilitated by a partially folded intermediate,which is conformationally similar to that found in early 13C-CEST NMR. Interestingly, this study finds the rate-limiting transitionfrom the unfolded state to this intermediate initiated by the formationof an A-minor twist interaction, a stable scaffold in the aptamerdomain, stabilized by specific Mg2+ coordination. The contactprobability map shows that this specific Mg2+ bridges ahelical region and an internal loop, mitigating electrostatic repulsionat the phosphate level. As a result, a set of hydrogen-bond-mediatedinteractions between the loop and the minor groove of the helix isstabilized, supporting the formation of the A-minor twist. This studyunderscores the critical role of Mg2+ in driving the rate-limitingevent of RNA folding and highlights its strategic location in stabilizingthe A-minor twist motif, essential for the global packing and regulatoryfunction of the SAM-II riboswitch aptamer.

The divergence in folding pathways between RNA co-transcriptional folding (CTF) and free folding (FF) is crucial for understanding dynamic functional regulation of RNAs. Here, we developed a simplified all-atom molecular dynamics framework to systematically compare the folding kinetics of an RNA hairpin (PDB:1ZIH) under CTF and FF conditions. By analyzing over 800 microseconds of simulated trajectory, we found that despite convergence to identical native conformations across CTF simulations (with varied transcription rates) and FF simulations, they exhibit distinct preferences for the folding pathways defined by the order of base-pair formation. Conformational space analysis shows that CTF biases the folding pathway by adopting more compact conformations than FF. Our findings provide atomic-scale insights into how temporal-spatial coupling of transcription and folding diversifies RNA folding dynamics.

Drosophila germ granules are enriched with mRNAs critical for development. Within them, mRNAs cluster through intermolecular interactions that may involve base pairing. Here we apply in silico, in vitro and in vivo approaches to examine the type and prevalence of these interactions. We show that RNA clustering can occur without extended sequence complementarity (stretches of six or more continuous complementary bases) and that mRNAs display similar level of foldedness within germ granules as outside. Our simulations predict that clustering is driven by scattered, surface-exposed bases, enabling intermolecular base pairing. Notably, engineered germ granule mRNAs containing exposed GC-rich complementary sequences within stem loops located in the 3′ untranslated region promote intermolecular interactions. However, these mRNAs are also expressed at lower levels, leading to developmental defects. Although germ granule mRNAs contain numerous GC-rich complementary sequences, RNA folding renders them inaccessible for intermolecular base pairing. We propose that RNA folding restricts intermolecular base pairing to maintain proper mRNA function within germ granules.

BackgroundRNA post-transcriptional modifications involve the addition of chemical groups to RNA molecules or alterations to their local structure. These modifications can change RNA base pairing, affect thermal stability, and influence RNA folding, thereby impacting alternative splicing, translation, cellular localization, stability, and interactions with proteins and other molecules. Accurate prediction of RNA modification sites is essential for understanding modification mechanisms.ResultsWe propose a novel deep learning model, YModPred, which accurately predicts multiple types of RNA modification sites in S. cerevisiae based on RNA sequences. YModPred combines convolution and self-attention mechanisms to enhance the model’s ability to capture global sequence information and improve local feature learning. The model can predict multi-type RNA modification sites. Comparative analysis against benchmark models demonstrates that YModPred outperforms existing state-of-the-art methods in predicting various RNA modification types. Additionally, the model’s prediction performance is further validated through visualization and motif analysis.ConclusionsYModPred is a deep learning-based model that effectively captures sequence features and dependencies, enabling accurate prediction of multi-type RNA modification sites in S. cerevisiae. We believe it will facilitate further research into the mechanisms of RNA modifications.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12915-025-02372-y.

While it is known that ions are required for folding of RNA, little is known about how transient/probabilistic ionic interactions facilitate biologically-relevant conformational rearrangements. To address this, we developed a theoretical model that employs all-atom resolution, with a simplified representation of biomolecular energetics, explicit electrostatics and ions (K+, Cl−, Mg2+). For well-studied RNA systems (58-mer and Ade riboswitch), the model accurately describes the concentration-dependent ionic environment, including (bidentate) chelated and hydrated (diffuse/outer-shell) ions. With this foundation, we applied the model to simulate the yeast ribosome and quantified the ion-dependent energy landscape of intersubunit rotation. These calculations show how the energetics of rotation responds to millimolar changes in [MgCl2], which shift the distribution between rotation states and alter the kinetics by more than an order of magnitude. We find that this response to the ionic concentration correlates with formation and breakage of ion-mediated interactions (inner-shell and outer-shell) between the ribosomal subunits. This analysis provides a physical basis for understanding how transient ion-mediated interactions can regulate a large-scale biological process.

[D1,2] stwintrons consist of nested U2 introns, where an internal intron splits the 5'-donor of an external intron between its first and second nucleotide. Almost all stwintrons described to date are of the [D1,2] type, suggesting unique means for their duplication. Sequence-similar [D1,2] stwintrons are typically integrated at new intron positions, specific for one species. Two hundred eighty-eight sequence-similar [D1,2] stwintrons were identified in the genomes of 14 Xylariales. Occasional missplicing was apparent, where almost the entire stwintron was excised as one canonical intron. Near-identical sister stwintrons were identified in Xylaria sp. MSU SB201401 and Xylaria longipes that share near-terminal inverted repeat elements of 10-nt length named 5'-NTIRE-10 and 3'-NTIRE-10, which are complementary as RNA. Complementary NTIRE-10 partners were also present in three Hypoxylaceae species. These NTIRE-10s can form a near-terminal double-stranded RNA stem structure that brings in close proximity the terminal G's of the [D1,2] stwintron and of its alternative misspliced intron. The exact folding of the interior stwintron RNA appears irrelevant. Ten of the stwintrons with complementary NTIRE-10s are present in Xylaria sp. MSU SB201401, implying that [D1,2] stwintron duplication occurs frequently in this species.IMPORTANCESpliceosomal introns are excised from pre-mRNAs by a ribonucleoprotein complex, the U2 spliceosome. Excision does not necessarily occur by one splicing reaction. We had identified and validated intronic sequences in fungi that consist of two nested U2 introns and called them spliceosomal twin introns (stwintrons). In this bioinformatics-based study, we identified and validated almost 300 [D1,2] stwintrons with sequence similarity in the genomes of 14 species in the Xylariales order of Ascomycota. Thirty-seven of them feature small, fully complementary RNA inverted repeat elements. These elements form a near-terminal RNA stem structure, bringing the terminal G's of the stwintron in close proximity. We further demonstrated the existence of an alternative splicing pattern involving one excision event that removes the two constituent introns from the transcript together. This work contributes to the understanding of mechanisms of stwintron gain in fungi.

Nascent RNA Folding and RNP Assembly Revealed by Single-molecule Microscopy.

Protein and RNA chaperones.

Cross-platform and polyhedral programming for Nussinov RNA folding

RNAs play crucial roles in various cellular actions, and the uncontrolled expression or improper folding of RNAs is a cause of many diseases. Certain oncogenic phenotypes stem from the overexpression of regulatory microRNAs that contain secondary structural elements. Thus, targeting disease-related microRNAs with small molecules is a potential therapeuticstrategy that has attracted growing interest. To probe the RNA-binding chemical space held in advanced small-molecule therapeutics, in this work, we screened the 78 FDA-approved small-molecule kinase inhibitors (SMKIs) as representatives of the most advanced kinase inhibitors for their binding affinity with pre-let-7 miRNA via a combination of computational methods and biophysical measurement. The best-ranked SMKIs based on docking scores were subjected to molecular dynamics simulation studies, followed by analysis of different computational parameters. Collectively, it provided reliable information on the binding affinity for the top-performed SMKI in the formation of SMKI-miRNA complexes with pre-let-7. Furthermore, the identification of the predicted most promising SMKI-miRNA interactions was validated by microscale thermophoresis, measuring direct binding affinities. This study evaluating the binding landscapes of the 78 FDA-approved SMKIs with pre-let-7 miRNA served as an example highlighting the necessity to characterize the biological targets of SMKIs, many of which are FDA-approved cancer agents, at the transcriptomic level with RNAs. The study also illustrates the possibility that the interaction with RNA targets may contribute to the observed biological and clinical performance of these approved SMKIs.

Small non-coding microRNAs (miRNAs) play crucial roles in the degradation of the messenger RNAs (mRNAs) that are involved in various biological processes post-transcriptionally and translationally. Many plants, especially Musa spp. (plantains and bananas), which are important perennial herbs of the family Musaceae, experience significant yield loss due to abiotic stressors, yet only a few miRNAs involved in this response have been identified. This study employed in silico analyses of transcriptome shotgun assembly (TSA) and expressed sequence tag (EST) sequences to identify Musa miRNAs and their target genes. Leaf and root tissues from three Musa genomic groups (AAA, AAB, and ABB) under drought stress were analyzed using quantitative real-time PCR (qRT-PCR) to validate the expression of miRNAs. A total of 17 potential conserved miRNAs from 11 families were identified, with the minimal folding free energies (-kcal/mol) of precursors ranging from -136.00 to -55.70, as observed through RNA folding analysis. Six miRNAs (miR530-5p, miR528-5p, miR482a, miR397a, miR160h, and miR399a) showed distinct tissue-specific expression patterns in the roots and leaves across the three groups. A total of 59 target regulatory transcription factors and enzymes involved in stress response, growth, and metabolism were predicted. Of these, 11 targets were validated for miR530-5p, miR528-5p, miR482a, and miR397a, using qRT-PCR. These four stress-responsive miRNAs exhibited an inverse expression relationship with their target genes across two different tissues in Musa groups. This research provides insights into miRNA-mediated drought stress responsiveness in Musa spp., potentially benefiting future studies on gene regulation under drought stress.

ObjectiveThis study investigated the association between p16 gene and its 450 C > G (rs11515) polymorphism with risk of oral cancer and precancerous oral lesions/oral potentially malignant disorder (OPMD).MethodThe study included 230 individuals with OPMD conditions (70 with leukoplakia, 90 with oral submucous fibrosis, and 70 with lichen planus), 72 oral cancer patients, and 300 cancer-free healthy controls. Genotyping of the p16 450 C > G polymorphism was conducted using PCR-RFLP methods, and genotype and allele frequencies were analyzed using chi-square test. Additionally, p16 gene expression levels were measured using RT-PCR among oral cancer patients, those with OPMD, and healthy controls. RNA fold was used to calculate the MFE of p16 mRNA.ResultsThe findings revealed that G allele of p16 450 C > G polymorphism significantly increased risk of oral diseases (oral cancer and OPMD) compared to C allele (OR 1.67, p = 0.0001). GG genotype was associated with higher risk of oral submucous fibrosis (OR 4.63, p = 0.0001), lichenplanus (OR 3.93, p = 0.0002), and leukoplakia (OR 2.38, p = 0.02) compared to CC genotype. Smokers and tobacco chewers carrying the G allele were at a significantly increased risk of developing OPMD (OR = 3.78 and 2.89). Notably, p16 transcript expression was significantly elevated (13.56-fold) in oral cancer patients compared to healthy controls. According to insilco analysis G allele gives more stable transcript of p16 (MEF − 64.90 kcal/mol) compared to C allele (MFE − 61.70 kcal/mol).ConclusionThese findings suggest that p16 gene and its 450 C > G polymorphism may be associated with risk of oral diseases, indicating their potential utility as biomarkers for these conditions.