RNA Tertiary Structure Research Articles

Pseudo-Rna Binding Domains Mediate Rna Structure Specificity in Upstream of N-Ras

RNA binding proteins (RBPs) commonly feature multiple RNA binding domains (RBDs), which provides these proteins with a modular architecture. Accumulating evidence supports that RBP architectural modularity and adaptability defines the specificity of their interactions with RNA. However, how multiple RBDs recognize their cognate single-stranded RNA (ssRNA) sequences in concert remains poorly understood. Here, we use Upstream of N-Ras (Unr) as a model system to address this question. Although reported to contain five ssRNA binding cold-shock domains (CSDs), we now demonstrate that Unr includes an additional four CSDs that do not bind RNA (pseudo-RBDs), but are involved in mediating RNA tertiary structure specificity by reducing the conformational heterogeneity of Unr. Disrupting canonical/non-canonical CSD interactions impacted RNA binding, Unr-mediated translation regulation, and the Unr-dependent RNA interactome. Taken together, our studies revealed a new paradigm in protein-RNA recognition, where interactions between RBDs and pseudo- RBDs select RNA tertiary structures, influence RNP assembly and define target specificity.

RNA size and 3-dimensional structure determine ultrafiltration behavior of small RNA molecules

Successful commercialization of RNA therapeutics will require the development of appropriate manufacturing and purification processes suitable for the production of large quantities of high quality and high purity RNA with well-defined tertiary structures. Ultrafiltration has the potential to play a major role in RNA processing, both for removal of large molecular weight species (with the RNA collected in the permeate) and for RNA concentration or buffer exchange (with the RNA collected in the retentate). Previous studies have demonstrated the potential of using tangential flow filtration (TFF) for RNA separations, but most of these data were obtained with crude RNA mixtures containing RNA with a range of size and structure. The objective of this study was to directly evaluate the effects of RNA size and tertiary structure on the ultrafiltration behavior over a range of solution conditions (e.g., added salt and urea). Transmission of a hairpin RNA with 70 nucleotides was much greater than that of a linear RNA having the same number of nucleotides, consistent with the smaller size as determined by dynamic light scattering. RNA transmission increased at high NaCl concentrations and in the presence of urea, particularly for the linear RNA. These results provide new insights into RNA ultrafiltration as well as a framework for the application of ultrafiltration for the purification of RNA therapeutics.

RNA-Puzzles toolkit: a computational resource of RNA 3D structure benchmark datasets, structure manipulation, and evaluation tools.

Significant improvements have been made in the efficiency and accuracy of RNA 3D structure prediction methods during the succeeding challenges of RNA-Puzzles, a community-wide effort on the assessment of blind prediction of RNA tertiary structures. The RNA-Puzzles contest has shown, among others, that the development and validation of computational methods for RNA fold prediction strongly depend on the benchmark datasets and the structure comparison algorithms. Yet, there has been no systematic benchmark set or decoy structures available for the 3D structure prediction of RNA, hindering the standardization of comparative tests in the modeling of RNA structure. Furthermore, there has not been a unified set of tools that allows deep and complete RNA structure analysis, and at the same time, that is easy to use. Here, we present RNA-Puzzles toolkit, a computational resource including (i) decoy sets generated by different RNA 3D structure prediction methods (raw, for-evaluation and standardized datasets), (ii) 3D structure normalization, analysis, manipulation, visualization tools (RNA_format, RNA_normalizer, rna-tools) and (iii) 3D structure comparison metric tools (RNAQUA, MCQ4Structures). This resource provides a full list of computational tools as well as a standard RNA 3D structure prediction assessment protocol for the community.

Identification and Characterization of New RNA Tetraloop Sequence Families.

There is an abundance of RNA sequence information available due to the efforts of sequencing projects. However, current techniques implemented to solve the tertiary structures of RNA, such as NMR and X-ray crystallography, are difficult and time-consuming. Therefore, biophysical techniques are not able to keep pace with the abundance of sequence information available. Because of this, there is a need to develop quick and efficient ways to predict RNA tertiary structure from sequence. One promising approach is to identify structural patterns within previously solved 3D structures and apply these patterns to new sequences. RNA tetraloops are one of the most common naturally occurring secondary structure motifs. Here, we use RNA Characterization of Secondary Structure Motifs (CoSSMos), Dissecting the Spatial Structure of RNA (DSSR), and a bioinformatic approach to search for and characterize tertiary structure patterns among tetraloops. Not surprising, we identified the well-known GNRA and UNCG tetraloops, as well as the previously identified RNYA tetraloop. However, some previously identified characteristics of these families were not observed in this data set, and some new characteristics were identified. In addition, we also identified and characterized three new tetraloop sequence families: YGAR, UGGU, and RMSA. This new structural information sheds light on the tertiary structure of tetraloops and contributes to the efforts of RNA tertiary structure prediction from sequence.

A unique internal ribosome entry site representing a dynamic equilibrium state of RNA tertiary structure in the 5'-UTR of Wheat yellow mosaic virus RNA1.

Internal ribosome entry sites (IRESes) were first reported in RNA viruses and subsequently identified in cellular mRNAs. In this study, IRES activity of the 5′-UTR in Wheat yellow mosaic virus (WYMV) RNA1 was identified, and the 3′-UTR synergistically enhanced this IRES activity via long-distance RNA–RNA interaction between C80U81and A7574G7575. Within the 5′-UTR, the hairpin 1(H1), flexible hairpin 2 (H2) and linker region (LR1) between H1 and H2 played an essential role in cap-independent translation, which is associated with the structural stability of H1, length of discontinuous stems and nucleotide specificity of the H2 upper loop and the long-distance RNA–RNA interaction sites in LR1. The H2 upper loop is a target region of the eIF4E. Cytosines (C55, C66, C105 and C108) in H1 and H2 and guanines (G73, G79 and G85) in LR1 form discontinuous and alternative base pairing to maintain the dynamic equilibrium state, which is used to elaborately regulate translation at a suitable level. The WYMV RNA1 5′-UTR contains a novel IRES, which is different from reported IRESes because of the dynamic equilibrium state. It is also suggested that robustness not at the maximum level of translation is the selection target during evolution of WYMV RNA1.

Computational design of three-dimensional RNA structure and function.

RNA nanotechnology seeks to create nanoscale machines by repurposing natural RNA modules. The field is slowed by the current need for human intuition during three-dimensional structural design. Here, we demonstrate that three distinct problems in RNA nanotechnology can be reduced to a pathfinding problem and automatically solved through an algorithm called RNAMake. First, RNAMake discovers highly stable single-chain solutions to the classic problem of aligning a tetraloop and its sequence-distal receptor, with experimental validation from chemical mapping, gel electrophoresis, solution X-ray scattering and crystallography with 2.55 Å resolution. Second, RNAMake automatically generates structured tethers that integrate 16S and 23S ribosomal RNAs into single-chain ribosomal RNAs that remain uncleaved by ribonucleases and assemble onto messenger RNA. Third, RNAMake enables the automated stabilization of small-molecule binding RNAs, with designed tertiary contacts that improve the binding affinity of the ATP aptamer and improve the fluorescence and stability of the Spinach RNA in cell extracts and in living Escherichia coli cells.

Multiplexed genome engineering by Cas12a and CRISPR arrays encoded on single transcripts.

The ability to modify multiple genetic elements simultaneously would help to elucidate and control the gene interactions and networks underlying complex cellular functions. However, current genome engineering technologies are limited in both the number and the type of perturbations that can be performed simultaneously. Here, we demonstrate that both Cas12a and a clustered regularly interspaced short palindromic repeat (CRISPR) array can be encoded in a single transcript by adding a stabilizer tertiary RNA structure. By leveraging this system, we illustrate constitutive, conditional, inducible, orthogonal and multiplexed genome engineering of endogenous targets using up to 25 individual CRISPR RNAs delivered on a single plasmid. Our method provides a powerful platform to investigate and orchestrate the sophisticated genetic programs underlying complex cell behaviors.

Sequence-dependent RNA helix conformational preferences predictably impact tertiary structure formation

Structured RNAs and RNA complexes underlie biological processes ranging from control of gene expression to protein translation. Approximately 50% of nucleotides within known structured RNAs are folded into Watson-Crick (WC) base pairs, and sequence changes that preserve these pairs are typically assumed to preserve higher-order RNA structure and binding of macromolecule partners. Here, we report that indirect effects of the helix sequence on RNA tertiary stability are, in fact, significant but are nevertheless predictable from a simple computational model called RNAMake-∆∆G. When tested through the RNA on a massively parallel array (RNA-MaP) experimental platform, blind predictions for >1500 variants of the tectoRNA heterodimer model system achieve high accuracy (rmsd 0.34 and 0.77 kcal/mol for sequence and length changes, respectively). Detailed comparison of predictions to experiments support a microscopic picture of how helix sequence changes subtly modulate conformational fluctuations at each base-pair step, which accumulate to impact RNA tertiary structure stability. Our study reveals a previously overlooked phenomenon in RNA structure formation and provides a framework of computation and experiment for understanding helix conformational preferences and their impact across biological RNA and RNA-protein assemblies.

Abstract 4494: HNRNPH1-dependent splicing of a fusion oncogene reveals a targetable RNA G-quadruplex interaction

Abstract Ewing sarcoma (EWS) is the second most common bone tumor in children and adolescents. The primary oncogenic event in ~85% of EWS is a chromosomal translocation that generates a fusion gene encoding the aberrant transcription factor EWS-FLI1. A third of EWS-FLI1 driven tumors harbor translocations that retain exon 8 of the EWSR1 gene, and in these tumors, skipping of this exon is vital to express an in-frame EWS-FLI1 mRNA. We have shown previously that the heterogeneous nuclear ribonucleoprotein H1 (HNRNPH1) binds to G-rich sequences within EWSR1 exon 8 and facilitates the exclusion of this exon from distinct EWS-FLI1 pre-mRNAs. Guanine-rich nucleic acids may fold into stable tertiary structures, such as RNA guanine quadruplexes (rG4s). Our current studies are focused on the tertiary RNA structure of the G-rich regions within EWSR1 exon 8 and its role in HNRNPH1-dependent RNA processing. Here, we show that the processing of distinct EWS-FLI1 pre-mRNAs by HNRNPH1, but not other homologous family members, resembles alternative splicing of transcript variants of wild-type EWSR1. We demonstrate that guanine-rich sequences within EWSR1 exon 8 can fold into RNA G-quadruplex structures and that this structure favors the recruitment of HNRNPH1. Bioinformatic analysis of transcriptome-wide profiles for RNA G-quadruplexes and RNA targets of HNRNPH1 revealed sequences containing two-quartet G-quadruplex configurations are central for HNRNPH1 binding to exonic elements. Critically, we also demonstrate that the glycine-tyrosine-arginine-rich domain of HNRNPH1 is the minimal domain required for G-quadruplex recognition. Small molecules that can displace HNRNPH1 binding may provide a therapeutic vulnerability in a subset of Ewing sarcoma. To evaluate if this protein-RNA interaction is amenable to small molecules, we performed displacement assays with HNRNPH1 protein and an EWSR1 exon 8 RNA oligomer at varying concentrations of the pan-quadruplex binding molecule, pyridostatin (PDS). PDS disrupts the HNRNPH1-RNA complex with an IC50 of 7 micromolar. Furthermore, treatment with PDS selectivity inhibits the growth of EWS cells harboring EWSR1 exon 8 fusions, decreases EWS-FLI1 activity in cell-based reporter assays, and restores mRNA expression of EWS-FLI1 deregulated transcriptional targets. Our findings illustrate that splicing modulation of EWS-FLI1 pre-mRNA is a promising strategy for future therapeutics against this fusion oncogene expressed in a third of Ewing sarcoma. Citation Format: Carla Neckles, Robert Boer, Nicholas Aboreden, Robert L. Walker, Bong-Hyun Kim, Suntae Kim, John S. Schneekloth, Natasha J. Caplen. HNRNPH1-dependent splicing of a fusion oncogene reveals a targetable RNA G-quadruplex interaction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4494.

Novel 13 C-detected NMR Experiments for the Precise Detection of RNA Structure.

Up to now, NMR spectroscopic investigations of RNA have utilized imino proton resonances as reporters for base pairing and RNA structure. The nucleobase amino groups are often neglected, since most of their resonances are broadened beyond detection due to rotational motion around the C–NH2 bond. Here, we present 13C‐detected NMR experiments for the characterization of all RNA amino groups irrespective of their motional behavior. We have developed a C(N)H‐HDQC experiment that enables the observation of a complete set of sharp amino resonances through the detection of proton‐NH2 double quantum coherences. Further, we present an “amino”‐NOESY experiment to detect NOEs to amino protons, which are undetectable by any other conventional NOESY experiment. Together, these experiments allow the exploration of additional chemical shift information and inter‐residual proton distances important for high‐resolution RNA secondary and tertiary structure determination.

Limits in accuracy and a strategy of RNA structure prediction using experimental information.

RNA structural complexity and flexibility present a challenge for computational modeling efforts. Experimental information and bioinformatics data can be used as restraints to improve the accuracy of RNA tertiary structure prediction. Regarding utilization of restraints, the fundamental questions are: (i) What is the limit in prediction accuracy that one can achieve with arbitrary number of restraints? (ii) Is there a strategy for selection of the minimal number of restraints that would result in the best structural model? We address the first question by testing the limits in prediction accuracy using native contacts as restraints. To address the second question, we develop an algorithm based on the distance variation allowed by secondary structure (DVASS), which ranks restraints according to their importance to RNA tertiary structure prediction. We find that due to kinetic traps, the greatest improvement in the structure prediction accuracy is achieved when we utilize only 40–60% of the total number of native contacts as restraints. When the restraints are sorted by DVASS algorithm, using only the first 20% ranked restraints can greatly improve the prediction accuracy. Our findings suggest that only a limited number of strategically selected distance restraints can significantly assist in RNA structure modeling.

Modulating RNA secondary and tertiary structures by mismatch binding ligands

Much recent attention has been focused on small organic molecules binding to non-canonical structures of nucleic acids, especially, RNA. The Human Genome Project and the ENCODE (encyclopedia of DNA elements) project revealed that more than 75% of the human genome is transcribed into RNA, while only ∼3% of the human genome encodes a protein. These non-protein-coding RNAs are thought to play significant roles in many cellular processes and are promising targets for drug discovery. Emerging roles of the non-coding RNAs in a variety of diseases provides enormous opportunities for pharmaceutical research on developing drugs targeting undruggable and rare diseases. During the last two decades, our laboratory has focused attention on small molecules binding to non-canonical DNA and RNA structures, especially to mismatched base pairs. Mismatch binding ligands (MBLs) we have developed are synthetic molecules designed in silico based on the hypothesis of hydrogen-bonding and semi-intercalation to DNA and RNA. Most of MBLs consists of two heterocycles having hydrogen bonding surfaces fully or partially complementary to that of nucleotide bases. In our design, each heterocycle binds to one of the mismatched bases by hydrogen bonding to form pseudo-base pairs, which would be stacked with the adjacent base pairs. The hypothesis allows us in principle to design small molecules binding to any mismatched base pairs, but it turned out not to be the case in reality. However, we have so far succeeded in developing several MBLs binding to DNA and RNA motifs of biological significance. In this review, we shall describe the hypothesis of molecular design of MBLs and its outcome regarding RNA targeting.

Using SHAPE-MaP to probe small molecule-RNA interactions.

RNA is a regulator and catalyst of many cellular processes. Efforts to therapeutically harness RNA began with the discovery of myriad coding and non-coding RNAs and their versatile modes of action. However, due to its dynamic structure and the polar and repetitive nature of its surface, RNA presents a challenging target for drug design. For an RNA to be druggable, it must contain a motif that assumes a nearly fixed and unique conformation that a small molecule can recognize and bind consistently and with high affinity. Hence, reliable methods for determining the secondary and tertiary structures of RNA, and even the features and occupancy of potential drug binding sites are of utmost importance for the effective design of RNA-based therapeutics. Selective 2'-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) has emerged as such a method, by which RNA secondary structure can be probed at single-nucleotide resolution, under a variety of conditions, and in the presence of RNA-specific small-molecule ligands. In this review, we describe an in-depth protocol for using SHAPE-MaP to characterize RNA-small molecule interactions in cell culture (in cellulo). This method can be applied to transcripts of any size or abundance, and to determine the sites and affinities of small molecule binding, making it an essential and versatile tool for drug discovery.

Synthetic ligands for PreQ1 riboswitches provide structural and mechanistic insights into targeting RNA tertiary structure

Riboswitches are naturally occurring RNA aptamers that regulate gene expression by binding to specific small molecules. Riboswitches control the expression of essential bacterial genes and are important models for RNA-small molecule recognition. Here, we report the discovery of a class of synthetic small molecules that bind to PreQ1 riboswitch aptamers. These molecules bind specifically and reversibly to the aptamers with high affinity and induce a conformational change. Furthermore, the ligands modulate riboswitch activity through transcriptional termination despite no obvious chemical similarity to the cognate ligand. X-ray crystallographic studies reveal that the ligands share a binding site with the cognate ligand but make different contacts. Finally, alteration of the chemical structure of the ligand causes changes in the mode of RNA binding and affects regulatory function. Thus, target- and structure-based approaches can be used to identify and understand the mechanism of synthetic ligands that bind to and regulate complex, folded RNAs.

Structural Studies on the HERV‐K Nuclear Export RNA Element

Human endogenous retroviruses (HERVs) are remnants of ancient germline infections that comprise 8% of the human genome. A number of HERVs are actively expressed—their products assume important physiological roles in embryonic development and have been associated with cancer and autoimmune diseases. Expression of a type of HERV, HERV‐K, has been associated with amyotrophic lateral sclerosis (ALS) and some cancers. Expression of the Env protein appears to be dependent on a cis‐acting signal, RcRe, and a viral protein called Rec that mediate nuclear export of unspliced mRNAs in Crm1‐dependent manner, similar to the Rev‐RRE system in HIV. Despite low sequence similarity, the HERV‐K RcRE and HIV RRE are both characterized by a long stem and several smaller stems centered around a junction at the top of the long stem. We recently reported the three‐dimensional structure of the HIV RRE RNA and found that it is a flat, “A”‐shaped molecule (Fang et al., 2013). Based on apparent secondary structure similarities, we hypothesized that the unique “A” shape may be conserved in complex retroviruses. We examined the tertiary structure of the RcRE RNA in solution using small‐angle X‐ray scattering. Our results suggest that the two divergent retroviral elements are structurally conserved, attesting to the significance of the three‐dimensional structure in Rev‐RRE recognition. We report a structure‐ and function‐based mutational analysis of the RcRE tertirary structure.Support or Funding InformationNaval Academy Research Council (NARC)DTRA CB Technologies Service Academy Research Initiative.US Naval Academy, Chemistry DepartmentThis abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

ToGo-WF: prediction of RNA tertiary structures and RNA-RNA/protein interactions using the KNIME workflow.

Recent progress in molecular biology has revealed that many non-coding RNAs regulate gene expression or catalyze biochemical reactions in tumors, viruses and several other diseases. The tertiary structure of RNA molecules and RNA–RNA/protein interaction sites are of increasing importance as potential targets for new medicines that treat a broad array of human diseases. Current RNA drugs are split into two groups: antisense RNA molecules and aptamers. In this report, we present a novel workflow to predict RNA tertiary structures and RNA–RNA/protein interactions using the KNIME environment, which enabled us to assemble a combination of RNA-related analytical tools and databases. In this study, three analytical workflows for comprehensive structural analysis of RNA are introduced: (1) prediction of the tertiary structure of RNA; (2) prediction of the structure of RNA–RNA complexes and analysis of their interactions; and (3) prediction of the structure of RNA–protein complexes and analysis of their interactions. In an RNA–protein case study, we modeled the tertiary structure of pegaptanib, an aptamer drug, and performed docking calculations of the pegaptanib-vascular endothelial growth factor complex using a fragment of the interaction site of the aptamer. We also present molecular dynamics simulations of the RNA–protein complex to evaluate the affinity of the complex by mutating bases at the interaction interface. The results provide valuable information for designing novel features of aptamer-protein complexes.Electronic supplementary materialThe online version of this article (10.1007/s10822-019-00195-y) contains supplementary material, which is available to authorized users.

Structural insights into FTO’s catalytic mechanism for the demethylation of multiple RNA substrates

FTO demethylates internal N6-methyladenosine (m6A) and N6,2'-O-dimethyladenosine (m6Am; at the cap +1 position) in mRNA, m6A and m6Am in snRNA, and N1-methyladenosine (m1A) in tRNA in vivo, and in vitro evidence supports that it can also demethylate N6-methyldeoxyadenosine (6mA), 3-methylthymine (3mT), and 3-methyluracil (m3U). However, it remains unclear how FTO variously recognizes and catalyzes these diverse substrates. Here we demonstrate-in vitro and in vivo-that FTO has extensive demethylation enzymatic activity on both internal m6A and cap m6Am Considering that 6mA, m6A, and m6Am all share the same nucleobase, we present a crystal structure of human FTO bound to 6mA-modified ssDNA, revealing the molecular basis of the catalytic demethylation of FTO toward multiple RNA substrates. We discovered that (i) N6-methyladenine is the most favorable nucleobase substrate of FTO, (ii) FTO displays the same demethylation activity toward internal m6A and m6Am in the same RNA sequence, suggesting that the substrate specificity of FTO primarily results from the interaction of residues in the catalytic pocket with the nucleobase (rather than the ribose ring), and (iii) the sequence and the tertiary structure of RNA can affect the catalytic activity of FTO. Our findings provide a structural basis for understanding the catalytic mechanism through which FTO demethylates its multiple substrates and pave the way forward for the structure-guided design of selective chemicals for functional studies and potential therapeutic applications.

The Role of Mg+2 Ion Interactions in Folding of the Twister Ribozyme and PreQ1 Riboswitch Revealed through Umbrella Sampling Combined with Oscillating Chemical Potential Grand Canonical Monte Carlo/Molecular Dynamics Simulations

Ribozymes, RNA molecules that work as enzymes, exhibit self-cleaving properties or catalytic mechanisms for processing of biomolecules. However it is challenging to resolve atomic-details of the folding landscape of ribozymes as they assume the tertiary structures required for catalytic activity. Metal ions, especially Mg+2 ions, are known to neutralize these negatively charged nucleic acids and specifically stabilize RNA tertiary structures. Earlier studies have determined specific binding sites of Mg+2 ions for RNAs, but are limited to folded conformations, such that their role in RNA folding processes is still unclear. Here, we use a computational approach that combines umbrella sampling with oscillating chemical potential Grand Canonical Monte Carlo/Molecular Dynamics (GCMC/MD) simulations to capture the atomic-level details of the intermediate states of RNA folding and identify the ion-RNA interactions that drive the folding pathway. The oscillating excess chemical potential allows for the sampling of Mg+2 ion distributions of the partially folded states of RNA without any bias from initial Mg+2-RNA configurations. We investigate the unfolding of two RNA molecules, the twister ribozyme and preQ1 riboswitch, along reaction coordinates used in experimental studies. We also simulate the ribozymes at different ion concentrations and capture the effect of ions on the folding potentials of mean force. Results reveal the stability of intermediate states and track the ion-mediated conformational changes. Overall, the present study establishes a better understanding of how Mg+2 ion-interactions contribute to RNA folding.

An RNA Scoring Function for Tertiary Structure Prediction Based on Multi-layer Neural Networks

A good scoring function is necessary for ab inito prediction of RNA tertiary structures. In this study, we explored the power of a machine learning based approach as a scoring function. Compared with the traditional scoring functions, the present approach is more flexible in incorporating different kinds of features; it is also free of the difficult problem of choosing the reference state. Two multi-layer neural networks were constructed and trained. They took RNA a structural candidate as input and then output its likeness score that evaluates the likeness of the candidate to the native structure. The first network was working at the coarse-grained level of RNA structures, while the second at the all-atom level. We also built an RNA database and split it into the training, validation, and testing sets, containing 322, 70, and 70 RNAs, respectively. Each RNA was accompanied with 300 decoys generated by high-temperature molecular dynamics simulations. The networks were trained on the training set and then optimized with an early-stop strategy, based on the loss of the validation set. We then tested the performance of the networks on the testing set. The results were found to be consistently better than a recent knowledge-based all-atom potential.

ScanFold: an approach for genome-wide discovery of local RNA structural elements-applications to Zika virus and HIV.

In addition to encoding RNA primary structures, genomes also encode RNA secondary and tertiary structures that play roles in gene regulation and, in the case of RNA viruses, genome replication. Methods for the identification of functional RNA structures in genomes typically rely on scanning analysis windows, where multiple partially-overlapping windows are used to predict RNA structures and folding metrics to deduce regions likely to form functional structure. Separate structural models are produced for each window, where the step size can greatly affect the returned model. This makes deducing unique local structures challenging, as the same nucleotides in each window can be alternatively base paired. We are presenting here a new approach where all base pairs from analysis windows are considered and weighted by favorable folding. This results in unique base pairing throughout the genome and the generation of local regions/structures that can be ranked by their propensity to form unusually thermodynamically stable folds. We applied this approach to the Zika virus (ZIKV) and HIV-1 genomes. ZIKV is linked to a variety of neurological ailments including microcephaly and Guillain–Barré syndrome and its (+)-sense RNA genome encodes two, previously described, functionally essential structured RNA regions. HIV, the cause of AIDS, contains multiple functional RNA motifs in its genome, which have been extensively studied. Our approach is able to successfully identify and model the structures of known functional motifs in both viruses, while also finding additional regions likely to form functional structures. All data have been archived at the RNAStructuromeDB (www.structurome.bb.iastate.edu), a repository of RNA folding data for humans and their pathogens.