Structure and stability of RNA/RNA kissing complex: with application to HIV dimerization initiation signal

Quantifying RNA structures and interactions with a unified reduced chain representation model

RNA is a pivotal molecule that plays critical roles in various cellular processes. Quantifying RNA structures and interactions is essential to understanding RNA function and developing RNA-based therapeutics. Using a unified five-bead model and a non-redundant database, this paper investigates the structural features and interactions of five commonly occurring RNA motifs, i.e., double-stranded helices, hairpin loops, internal/bulge loops, multi-branched junctions, and single-stranded terminal tails. Analyzing detailed distributions of RNA local structural features and base-base interactions reveals a preference for helical structures in both local backbone structures and base orientations. The interactions between adjacent bases exhibit motif-specific and sequence-dependent characteristics, reflecting the distinct topological constraints imposed by different loop-helix connection modes and the varying pairing and stacking interactions among different sequences. These findings shed light on the stability of RNA helices, emphasizing their significance in providing dominant base pairing and stacking interactions for RNA structures and stability. The four non-helix motifs encompass unpaired nucleotide loops and exhibit diverse base-base interactions, contributing to the structural diversity observed in RNA. Overall, the complexity of RNA structure arises from the intricate interplay of base-base interactions.

RNA Folding Based on 5 Beads Model and Multiscale Simulation

RNA folding prediction is very meaningful and challenging. The molecular dynamics simulation (MDS) of all atoms (AA) is limited to the folding of small RNA molecules. At present, most of the practical models are coarse grained (CG) model, and the coarse-grained force field (CGFF) parameters usually depend on known RNA structures. However, the limitation of the CGFF is obvious that it is difficult to study the modified RNA. Based on the 3 beads model (AIMS_RNA_B3), we proposed the AIMS_RNA_B5 model with three beads representing a base and two beads representing the main chain (sugar group and phosphate group). We first run the all atom molecular dynamic simulation (AAMDS), and fit the CGFF parameter with the AA trajectory. Then perform the coarse-grained molecular dynamic simulation (CGMDS). AAMDS is the foundation of CGMDS. CGMDS is mainly to carry out the conformation sampling based on the current AAMDS state and improve the folding speed. We simulated the folding of three RNAs, which belong to hairpin, pseudoknot and tRNA respectively. Compared to the AIMS_RNA_B3 model, the AIMS_RNA_B5 model is more reasonable and performs better.

cRNAsp12 Web Server for the Prediction of Circular RNA Secondary Structures and Stabilities

Circular RNAs (circRNAs) are a novel class of non-coding RNA that, unlike linear RNAs, form a covalently closed loop without the 5' and 3' ends. Growing evidence shows that circular RNAs play important roles in life processes and have great potential implications in clinical and research fields. The accurate modeling of circRNAs structure and stability has far-reaching impact on our understanding of their functions and our ability to develop RNA-based therapeutics. The cRNAsp12 server offers a user-friendly web interface to predict circular RNA secondary structures and folding stabilities from the sequence. Through the helix-based landscape partitioning strategy, the server generates distinct ensembles of structures and predicts the minimal free energy structures for each ensemble with the recursive partition function calculation and backtracking algorithms. For structure predictions in the limited structural ensemble, the server also provides users with the option to set the structural constraints of forcing the base pairs and/or forcing the unpaired bases, such that only structures that meet the criteria are enumerated recursively.

Structural, Dynamical, and Entropic Differences between SARS-CoV and SARS-CoV-2 s2m Elements Using Molecular Dynamics Simulations

The functional role of the highly conserved stem-loop II motif (s2m) in SARS-CoV and SARS-CoV-2 in the viral lifecycle remains enigmatic and an intense area of research. Structure and dynamics of the s2m are key to establishing a structure-function connection, yet a full set of atomistic resolution coordinates is not available for SARS-CoV-2 s2m. Our work constructs three-dimensional coordinates consistent with NMR solution phase data for SARS-CoV-2 s2m and provides a comparative analysis with its counterpart SARS-CoV s2m. We employed initial coordinates based on PDB ID 1XJR for SARS-CoV s2m and two models for SARS-CoV-2 s2m: one based on 1XJR in which we introduced the mutations present in SARS-CoV-2 s2m and the second based on the available SARS-CoV-2 NMR NOE data supplemented with knowledge-based methods. For each of the three systems, 3.5 μs molecular dynamics simulations were used to sample the structure and dynamics, and principal component analysis (PCA) reduced the ensembles to hierarchal conformational substates for detailed analysis. Dilute solution simulations of SARS-CoV s2m demonstrate that the GNRA-like terminal pentaloop is rigidly defined by base stacking uniquely positioned for possible kissing dimer formation. However, the SARS-CoV-2 s2m simulation did not retain the reported crystallographic SARS-CoV motifs and the terminal loop expands to a highly dynamic "nonaloop." Increased flexibility and structural disorganization are observed for the larger terminal loop, where an entropic penalty is computed to explain the experimentally observed reduction in kissing complex formation. Overall, both SARS-CoV and SARS-CoV-2 s2m elements have a similarly pronounced L-shape due to different motif interactions. Our study establishes the atomistic three-dimensional structure and uncovers dynamic differences that arise from s2m sequence changes, which sets the stage for the interrogation of different mechanistic pathways of suspected biological function.

A liquid crystal world for the origins of life

Nucleic acids (NAs) in modern biology accomplish a variety of tasks, and the emergence of primitive nucleic acids is broadly recognized as a crucial step for the emergence of life. While modern NAs have been optimized by evolution to accomplish various biological functions, such as catalysis or transmission of genetic information, primitive NAs could have emerged and been selected based on more rudimental chemical-physical properties, such as their propensity to self-assemble into supramolecular structures. One such supramolecular structure available to primitive NAs are liquid crystal (LC) phases, which are the outcome of the collective behavior of short DNA or RNA oligomers or monomers that self-assemble into linear aggregates by combinations of pairing and stacking. Formation of NA LCs could have provided many essential advantages for a primitive evolving system, including the selection of potential genetic polymers based on structure, protection by compartmentalization, elongation, and recombination by enhanced abiotic ligation. Here, we review recent studies on NA LC assembly, structure, and functions with potential prebiotic relevance. Finally, we discuss environmental or geological conditions on early Earth that could have promoted (or inhibited) primitive NA LC formation and highlight future investigation axes essential to further understanding of how LCs could have contributed to the emergence of life.

Biomotors, viral assembly, and RNA nanobiotechnology: Current achievements and future directions

The International Society of RNA Nanotechnology and Nanomedicine (ISRNN) serves to further the development of a wide variety of functional nucleic acids and other related nanotechnology platforms. To aid in the dissemination of the most recent advancements, a biennial discussion focused on biomotors, viral assembly, and RNA nanobiotechnology has been established where international experts in interdisciplinary fields such as structural biology, biophysical chemistry, nanotechnology, cell and cancer biology, and pharmacology share their latest accomplishments and future perspectives. The results summarized here highlight advancements in our understanding of viral biology and the structure-function relationship of frame-shifting elements in genomic viral RNA, improvements in the predictions of SHAPE analysis of 3D RNA structures, and the understanding of dynamic RNA structures through a variety of experimental and computational means. Additionally, recent advances in the drug delivery, vaccine design, nanopore technologies, biomotor and biomachine development, DNA packaging, RNA nanotechnology, and drug delivery are included in this critical review. We emphasize some of the novel accomplishments, major discussion topics, and present current challenges and perspectives of these emerging fields.

Ribonucleic Acid Folding Prediction Based on Iterative Multiscale Simulation

RNA folding prediction is a challenge. Currently, many RNA folding models are coarse-grained (CG) with the potential derived from the known RNA structures. However, this potential is not suitable for modified and entirely new RNA. It is also not suitable for the folding simulation of RNA in the real cellular environment, including many kinds of molecular interactions. In contrast, our proposed model has the potential to address these issues, which is a multiscale simulation scheme based on all-atom (AA) force fields. We fit the CG force field using the trajectories generated by the AA force field and then iteratively perform molecular dynamics (MD) simulations of the two scales. The all-atom molecular dynamics (AAMD) simulation is mainly responsible for the correction of RNA structure, and the CGMD simulation is mainly responsible for efficient conformational sampling. On the basis of this scheme, we can successfully fold three RNAs belonging to a hairpin, a pseudoknot, and a four-way junction.

VfoldMCPX: predicting multistrand RNA complexes

Multistrand RNA complexes play a critical role in RNA-related biological processes. The understanding of RNA functions and the rational design of RNA nanostructures require accurate prediction of the structure and folding stability of the complexes, including those containing pseudoknots. Here, we present VfoldMCPX, a new model for predicting two-dimensional (2D) structures and folding stabilities of multistrand RNA complexes. Based on a partition function-based algorithm combined with physical loop free energy parameters, the VfoldMCPX model predicts not only the native structure but also the folding stability of the complex. An important advantage of the model is the ability to treat pseudoknotted structures. Extensive tests on structure predictions show the VfoldMCPX model provides improved accuracy for multistranded RNA complexes, especially for RNA complexes with three or more strands and/or containing pseudoknots. We have developed a freely accessible VfoldMCPX web server at http://rna.physics.missouri.edu/vfoldMCPX2.

Landscape Zooming toward the Prediction of RNA Cotranscriptional Folding

RNA molecules fold as they are transcribed. Cotranscriptional folding of RNA plays a critical role in RNA functions in vivo. Present computational strategies focus on simulations where large structural changes may not be completely sampled. Here, we describe an alternative approach to predicting cotranscriptional RNA folding by zooming in and out of the RNA folding energy landscape. By classifying the RNA structural ensemble into "partitions" based on long, stable helices, we zoom out of the landscape and predict the overall slow folding kinetics from the interpartition kinetic network, and for each interpartition transition, we zoom in on the landscape to simulate the kinetics. Applications of the model to the 117-nucleotide E. coli SRP RNA and the 59-nucleotide HIV-1 TAR RNA show agreements with the experimental data and new structural and kinetic insights into biologically significant conformational switches and pathways for these important systems. This approach, by zooming in/out of an RNA folding landscape at different resolutions, might allow us to treat large RNAs in vivo with transcriptional pause, transcription speed, and other in vivo effects.

Vfold2D-MC: A Physics-Based Hybrid Model for Predicting RNA Secondary Structure Folding

Accurate prediction of RNA structure and folding stability has a far-reaching impact on our understanding of RNA functions. Here we develop Vfold2D-MC, a new physics-based model, to predict RNA structure and folding thermodynamics from the sequence. The model employs virtual bond-based coarse-graining of RNA backbone conformation and generates RNA conformations through Monte Carlo sampling of the bond angles and torsional angles of the virtual bonds. Using a coarse-grained statistical potential derived from the known structures, we assign each conformation with a statistical weight. The weighted average over the conformational ensemble gives the entropy and free energy parameters for the hairpin, bulge, and internal loops, and multiway junctions. From the thermodynamic parameters, we predict RNA structures, melting curves, and structural changes from the sequence. Theory-experiment comparisons indicate that Vfold2D-MC not only gives improved structure predictions but also enables the interpretation of thermodynamic results for different RNA structures, including multibranched junctions. This new model sets a promising framework to treat more complicated RNA structures, such as pseudoknotted and intramolecular kissing loops, for which experimental thermodynamic parameters are often unavailable.

The three-way junction structure of the HIV-1 PBS-segment binds host enzyme important for viral infectivity

HIV-1 reverse transcription initiates at the primer binding site (PBS) in the viral genomic RNA (gRNA). Although the structure of the PBS-segment undergoes substantial rearrangement upon tRNALys3 annealing, the proper folding of the PBS-segment during gRNA packaging is important as it ensures loading of beneficial host factors. DHX9/RNA helicase A (RHA) is recruited to gRNA to enhance the processivity of reverse transcriptase. Because the molecular details of the interactions have yet to be defined, we solved the solution structure of the PBS-segment preferentially bound by RHA. Evidence is provided that PBS-segment adopts a previously undefined adenosine-rich three-way junction structure encompassing the primer activation stem (PAS), tRNA-like element (TLE) and tRNA annealing arm. Disruption of the PBS-segment three-way junction structure diminished reverse transcription products and led to reduced viral infectivity. Because of the existence of the tRNA annealing arm, the TLE and PAS form a bent helical structure that undergoes shape-dependent recognition by RHA double-stranded RNA binding domain 1 (dsRBD1). Mutagenesis and phylogenetic analyses provide evidence for conservation of the PBS-segment three-way junction structure that is preferentially bound by RHA in support of efficient reverse transcription, the hallmark step of HIV-1 replication.

A malachite green light-up aptasensor for the detection of theophylline

Biosensors are of interest for the quantitative detection of small molecules (metabolites, drugs and contaminants for instance). To this end, fluorescence is a widely used technique that is easily associated to aptamers. Light-up aptamers constitute a particular class of oligonucleotides that, specifically induce fluorescence emission when binding to cognate fluorogenic ligands such as malachite green (MG). We engineered a dual aptasensor for theophylline (Th) based on the combination of switching hairpin aptamers specific for MG on the one hand and for Th on the other hand, hence their names: malaswitch (Msw) and theoswitch (Thsw). The two aptaswitches form a loop-loop or kissing Msw-Thsw complex only in the presence of theophylline, allowing binding of MG, subsequently generating a fluorescent signal. The combination of the best Msw and Thsw variants, MswG12 and Thsw19.1, results in a 20-fold fluorescence enhancement of MG at saturating theophylline concentration. This aptasensor discriminates between theophylline and its analogues caffeine and theobromine. Kissing aptaswitches derived from light-up aptamers constitute a novel sensing device.

Hypoxia-inducible factor-1α-dependent induction of miR122 enhances hepatic ischemia tolerance

Hepatic ischemia and reperfusion (IR) injury contributes to the morbidity and mortality associated with liver transplantation. microRNAs (miRNAs) constitute a family of noncoding RNAs that regulate gene expression at the posttranslational level through the repression of specific target genes. Here, we hypothesized that miRNAs could be targeted to enhance hepatic ischemia tolerance. A miRNA screen in a murine model of hepatic IR injury pointed us toward the liver-specific miRNA miR122. Subsequent studies in mice with hepatocyte-specific deletion of miR122 (miR122loxP/loxP Alb-Cre+ mice) during hepatic ischemia and reperfusion revealed exacerbated liver injury. Transcriptional studies implicated hypoxia-inducible factor-1α (HIF1α) in the induction of miR122 and identified the oxygen-sensing prolyl hydroxylase domain 1 (PHD1) as a miR122 target. Further studies indicated that HIF1α-dependent induction of miR122 participated in a feed-forward pathway for liver protection via the enhancement of hepatic HIF responses through PHD1 repression. Moreover, pharmacologic studies utilizing nanoparticle-mediated miR122 overexpression demonstrated attenuated liver injury. Finally, proof-of-principle studies in patients undergoing orthotopic liver transplantation showed elevated miR122 levels in conjunction with the repression of PHD1 in post-ischemic liver biopsies. Taken together, the present findings provide molecular insight into the functional role of miR122 in enhancing hepatic ischemia tolerance and suggest the potential utility of pharmacologic interventions targeting miR122 to dampen hepatic injury during liver transplantation.

IsRNA1: De Novo Prediction and Blind Screening of RNA 3D Structures

Modeling structures and functions of large ribonucleic acid (RNAs) especially with complicated topologies is highly challenging due to the inefficiency of large conformational sampling and the presence of complicated tertiary interactions. To address this problem, one highly promising approach is coarse-grained modeling. Here, following an iterative simulated reference state approach to decipher the correlations between different structural parameters, we developed a potent coarse-grained RNA model named as IsRNA1 for RNA studies. Molecular dynamics simulations in the IsRNA1 can predict the native structures of small RNAs from a sequence and fold medium-sized RNAs into near-native tertiary structures with the assistance of secondary structure constraints. A large-scale benchmark test on RNA 3D structure prediction shows that IsRNA1 exhibits improved performance for relatively large RNAs of complicated topologies, such as large stem-loop structures and structures containing long-range tertiary interactions. The advantages of IsRNA1 include the consideration of the correlations between the different structural variables, the appropriate characterization of canonical base-pairing and base-stacking interactions, and the better sampling for the backbone conformations. Moreover, a blind screening protocol was developed based on IsRNA1 to identify good structural models from a pool of candidates without prior knowledge of the native structures.

Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability

The ability to accurately predict RNA hairpin structure and stability for different loop sequences and salt conditions is important for understanding, modeling, and designing larger RNA folds. However, traditional RNA secondary structure models cannot treat loop-sequence and ionic effects on RNA hairpin folding. Here, we describe a general, three-dimensional (3D) conformation-based computational method for modeling salt concentration-dependent conformational distributions and the detailed 3D structures for a set of three RNA hairpins that contain a variable, 15-nucleotide loop sequence. For a given RNA sequence, the new, to our knowledge, method integrates a Vfold2D two-dimensional structure folding model with IsRNA coarse-grained molecular dynamics 3D folding simulations and Monte Carlo tightly bound ion estimations of ion-mediated electrostatic interactions. The model predicts free-energy landscapes for the different RNA hairpin-forming sequences with variable salt conditions. The theoretically predicted results agree with the experimental fluorescence measurements, validating the strategy. Furthermore, the theoretical model goes beyond the experimental results by enabling in-depth 3D structural analysis, revealing energetic mechanisms for the sequence- and salt-dependent folding stability. Although the computational framework presented here is developed for RNA hairpin systems, the general method may be applied to investigate other RNA systems, such as multiway junctions or pseudoknots in mixed metal ion solutions.

Topological constraints of RNA pseudoknotted and loop-kissing motifs: applications to three-dimensional structure prediction

An RNA global fold can be described at the level of helix orientations and relatively flexible loop conformations that connect the helices. The linkage between the helices plays an essential role in determining the structural topology, which restricts RNA local and global folds, especially for RNA tertiary structures involving cross-linked base pairs. We quantitatively analyze the topological constraints on RNA 3D conformational space, in particular, on the distribution of helix orientations, for pseudoknots and loop-loop kissing structures. The result shows that a viable conformational space is predominantly determined by the motif type, helix size, and loop size, indicating a strong topological coupling between helices and loops in RNA tertiary motifs. Moreover, the analysis indicates that (cross-linked) tertiary contacts can cause much stronger topological constraints on RNA global fold than non-cross-linked base pairs. Furthermore, based on the topological constraints encoded in the 2D structure and the 3D templates, we develop a 3D structure prediction approach. This approach can be further combined with structure probing methods to expand the capability of computational prediction for large RNA folds.

Structure folding of RNA kissing complexes in salt solutions: predicting 3D structure, stability, and folding pathway

RNA kissing complexes are essential for genomic RNA dimerization and regulation of gene expression, and their structures and stability are critical to their biological functions. In this work, we used our previously developed coarse-grained model with an implicit structure-based electrostatic potential to predict three-dimensional (3D) structures and stability of RNA kissing complexes in salt solutions. For extensive RNA kissing complexes, our model shows great reliability in predicting 3D structures from their sequences, and our additional predictions indicate that the model can capture the dependence of 3D structures of RNA kissing complexes on monovalent/divalent ion concentrations. Moreover, the comparisons with extensive experimental data show that the model can make reliable predictions on the stability for various RNA kissing complexes over wide ranges of monovalent/divalent ion concentrations. Notably, for RNA kissing complexes, our further analyses show the important contribution of coaxial stacking to the 3D structures and stronger stability than the corresponding kissing-interface duplexes at high salts. Furthermore, our comprehensive analyses for RNA kissing complexes reveal that the thermally folding pathway for a complex sequence is mainly determined by the relative stability of two possible folded states of kissing complex and extended duplex, which can be significantly modulated by its sequence.

A Polymer Physics Framework for the Entropy of Arbitrary Pseudoknots

The accurate prediction of RNA secondary structure from primary sequence has had enormous impact on research from the past 40 years. Although many algorithms are available to make these predictions, the inclusion of non-nested loops, termed pseudoknots, still poses challenges arising from two main factors: 1) no physical model exists to estimate the loop entropies of complex intramolecular pseudoknots, and 2) their NP-complete enumeration has impeded their study. Here, we address both challenges. First, we develop a polymer physics model that can address arbitrarily complex pseudoknots using only two parameters corresponding to concrete physical quantities-over an order of magnitude fewer than the sparsest state-of-the-art phenomenological methods. Second, by coupling this model to exhaustive enumeration of the set of possible structures, we compute the entire free energy landscape of secondary structures resulting from a primary RNA sequence. We demonstrate that for RNA structures of ∼80 nucleotides, with minimal heuristics, the complete enumeration of possible secondary structures can be accomplished quickly despite the NP-complete nature of the problem. We further show that despite our loop entropy model's parametric sparsity, it performs better than or on par with previously published methods in predicting both pseudoknotted and non-pseudoknotted structures on a benchmark data set of RNA structures of ≤80 nucleotides. We suggest ways in which the accuracy of the model can be further improved.

Effects of complementary loop composition in truncated R3C ligase ribozymes on kiss switch activation

The formation of a kissing-loop through the introduction of complementary 7-membered loops is known to dramatically increase the activity of truncated R3C ligase ribozymes that otherwise display reduced activity. Restoration of activity is thought to result from kissing complex formation-induced rearrangement of two molecules with complementary loops. By combining two types of R3C ligase ribozyme mutants, <A> and <hairpin-ΔU>, the influence of loop composition on ligation activity was investigated. Substrate ligation occurred in <hairpin-ΔU>, but not in <A>, despite the absence of a substrate-binding site in <hairpin-ΔU>. Loop-loop interactions of <A>- and <hairpin-ΔU>-variants with complementary 6-membered loops also resulted in proper kissing-complex formation-induced substrate ligation. However, heterogeneous combinations of 7- and 6-membered loops, and/or of 6- and 5-membered loops had distinct results that depended upon the sequence and bulged nucleotides of the loop regions. These differences suggest that both thermodynamic and kinetic controls act upon the kissing-loop interaction-mediated rearrangement of the shortened trans-R3C ribozymes.

Thermodynamic investigation of kissing-loop interactions

Kissing loop interactions (KLIs) are a common motif that is critical in retroviral dimerization, viroid replication, mRNA, and riboswitches. In addition, KLIs are currently used in a variety of biotechnology applications, such as in aptamer sensors, RNA scaffolds and to stabilize vaccines for therapeutics. Here we describe the thermodynamics of a basic intramolecular DNA capable of engaging in a KLI, consisting of two hairpins connected by a flexible linker. Each hairpin loop has a five-nucleotide complementary sequence theoretically capable of engaging in a KLI. On either side of each loop is two thymines which will not engage in kissing but are present to provide more flexibility and optimal KLI positioning. Our results suggest that the KLI occurs even at physiological salt levels, and that the KLI does not alter the thermodynamics and stability of the two stem structures. The KLI does not involve all five nucleotides, or at least each base-pair stack is not making full contact. Adding a second strand complementary to the bottom of the kissing complex removes flexibility and causes destabilization of the stems. The KLI of this less flexible complex is maintained but the T_M is reduced, indicating an entopic penalty to its formation.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Predicting RNA Structure with Vfold

In order to carry out biological functions, RNA molecules must fold into specific three-dimensional (3D) structures. Current experimental methods to determine RNA 3D structures are expensive and time consuming. With the recent advances in computational biology, RNA structure prediction is becoming increasingly reliable. This chapter describes a recently developed RNA structure prediction software, Vfold, a virtual bond-based RNA folding model. The main features of Vfold are the physics-based loop free energy calculations for various RNA structure motifs and a template-based assembly method for RNA 3D structure prediction. For illustration, we use the yybP-ykoY Orphan riboswitch as an example to show the implementation of the Vfold model in RNA structure prediction from the sequence.

VfoldCPX Server: Predicting RNA-RNA Complex Structure and Stability

RNA-RNA interactions are essential for genomic RNA dimerization, mRNA splicing, and many RNA-related gene expression and regulation processes. The prediction of the structure and folding stability of RNA-RNA complexes is a problem of significant biological importance and receives substantial interest in the biological community. The VfoldCPX server provides a new web interface to predict the two-dimensional (2D) structures of RNA-RNA complexes from the nucleotide sequences. The VfoldCPX server has several novel advantages including the ability to treat RNAs with tertiary contacts (crossing base pairs) such as loop-loop kissing interactions and the use of physical loop entropy parameters. Based on a partition function-based algorithm, the server enables prediction for structure with and without tertiary contacts. Furthermore, the server outputs a set of energetically stable structures, ranked by their stabilities. The results allow users to gain extensive physical insights into RNA-RNA interactions and their roles in RNA function. The web server is freely accessible at “http://rna.physics.missouri.edu/vfoldCPX”.

Structural computational modeling of RNA aptamers

RNA aptamers represent an emerging class of biologics that can be easily adapted for personalized and precision medicine. Several therapeutic aptamers with desirable binding and functional properties have been developed and evaluated in preclinical studies over the past 25years. However, for the majority of these aptamers, their clinical potential has yet to be realized. A significant hurdle to the clinical adoption of this novel class of biologicals is the limited information on their secondary and tertiary structure. Knowledge of the RNA's structure would greatly facilitate and expedite the post-selection optimization steps required for translation, including truncation (to reduce costs of manufacturing), chemical modification (to enhance stability and improve safety) and chemical conjugation (to improve drug properties for combinatorial therapy). Here we describe a structural computational modeling methodology that when coupled to a standard functional assay, can be used to determine key sequence and structural motifs of an RNA aptamer. We applied this methodology to enable the truncation of an aptamer to prostate specific membrane antigen (PSMA) with great potential for targeted therapy that had failed previous truncation attempts. This methodology can be easily applied to optimize other aptamers with therapeutic potential.

DNA-DNA kissing complexes as a new tool for the assembly of DNA nanostructures

Kissing-loop annealing of nucleic acids occurs in nature in several viruses and in prokaryotic replication, among other circumstances. Nucleobases of two nucleic acid strands (loops) interact with each other, although the two strands cannot wrap around each other completely because of the adjacent double-stranded regions (stems). In this study, we exploited DNA kissing-loop interaction for nanotechnological application. We functionalized the vertices of DNA tetrahedrons with DNA stem-loop sequences. The complementary loop sequence design allowed the hybridization of different tetrahedrons via kissing-loop interaction, which might be further exploited for nanotechnology applications like cargo transport and logical elements. Importantly, we were able to manipulate the stability of those kissing-loop complexes based on the choice and concentration of cations, the temperature and the number of complementary loops per tetrahedron either at the same or at different vertices. Moreover, variations in loop sequences allowed the characterization of necessary sequences within the loop as well as additional stability control of the kissing complexes. Therefore, the properties of the presented nanostructures make them an important tool for DNA nanotechnology.

A Method to Predict the Structure and Stability of RNA/RNA Complexes

RNA/RNA interactions are essential for genomic RNA dimerization and regulation of gene expression. Intermolecular loop-loop base pairing is a widespread and functionally important tertiary structure motif in RNA machinery. However, computational prediction of intermolecular loop-loop base pairing is challenged by the entropy and free energy calculation due to the conformational constraint and the intermolecular interactions. In this chapter, we describe a recently developed statistical mechanics-based method for the prediction of RNA/RNA complex structures and stabilities. The method is based on the virtual bond RNA folding model (Vfold). The main emphasis in the method is placed on the evaluation of the entropy and free energy for the loops, especially tertiary kissing loops. The method also uses recursive partition function calculations and two-step screening algorithm for large, complicated structures of RNA/RNA complexes. As case studies, we use the HIV-1 Mal dimer and the siRNA/HIV-1 mutant (T4) to illustrate the method.

Physics-based RNA structure prediction

Despite the success of RNA secondary structure prediction for simple, short RNAs, the problem of predicting RNAs with long-range tertiary folds remains. Furthermore, RNA 3D structure prediction is hampered by the lack of the knowledge about the tertiary contacts and their thermodynamic parameters. Low-resolution structural modeling enables us to estimate the conformational entropies for a number of tertiary folds through rigorous statistical mechanical calculations. The models lead to 3D tertiary folds at coarse-grained level. The coarse-grained structures serve as the initial structures for all-atom molecular dynamics refinement to build the final all-atom 3D structures. In this paper, we present an overview of RNA computational models for secondary and tertiary structures’ predictions and then focus on a recently developed RNA statistical mechanical model—the Vfold model. The main emphasis is placed on the physics behind the models, including the treatment of the non-canonical interactions in secondary and tertiary structure modelings, and the correlations to RNA functions.

A Method to Predict the 3D Structure of an RNA Scaffold

The ever increasing discoveries of noncoding RNA functions draw a strong demand for RNA structure determination from the sequence. In recently years, computational studies for RNA structures, at both the two-dimensional and the three-dimensional levels, led to several highly promising new developments. In this chapter, we describe a recently developed RNA structure prediction method based on the virtual bond-based coarse-grained folding model (Vfold). The main emphasis in the Vfold method is placed on the loop entropy calculations, the treatment of noncanonical (mismatch) interactions and the 3D structure assembly from motif-based template library. As case studies, we use the glycine riboswitch and the G310-U376 domain of MLV RNA to illustrate the Vfold-based prediction of RNA 3D structures from the sequences.

Vfold: a web server for RNA structure and folding thermodynamics prediction

BACKGROUND

The ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies.

RESULTS

The Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization.

CONCLUSIONS

The Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at "http://rna.physics.missouri.edu".

Many-body effect in ion binding to RNA

Ion-mediated electrostatic interactions play an important role in RNA folding stability. For a RNA in a solution with higher Mg(2+) ion concentration, more counterions in the solution can bind to the RNA, causing a strong many-body coupling between the bound ions. The many-body effect can change the effective potential of mean force between the tightly bound ions. This effect tends to dampen ion binding and lower RNA folding stability. Neglecting the many-body effect leads to a systematic error (over-estimation) of RNA folding stability at high Mg(2+) ion concentrations. Using the tightly bound ion model combined with a conformational ensemble model, we investigate the influence of the many-body effect on the ion-dependent RNA folding stability. Comparisons with the experimental data indicate that including the many-body effect led to much improved predictions for RNA folding stability at high Mg(2+) ion concentrations. The results suggest that the many-body effect can be important for RNA folding in high concentrations of multivalent ions. Further investigation showed that the many-body effect can influence the spatial distribution of the tightly bound ions and the effect is more pronounced for compact RNA structures and structures prone to the formation of local clustering of ions.

Predicting structure and stability for RNA complexes with intermolecular loop-loop base-pairing

RNA loop-loop interactions are essential for genomic RNA dimerization and regulation of gene expression. In this article, a statistical mechanics-based computational method that predicts the structures and thermodynamic stabilities of RNA complexes with loop-loop kissing interactions is described. The method accounts for the entropy changes for the formation of loop-loop interactions, which is a notable advancement that other computational models have neglected. Benchmark tests with several experimentally validated systems show that the inclusion of the entropy parameters can indeed improve predictions for RNA complexes. Furthermore, the method can predict not only the native structures of RNA/RNA complexes but also alternative metastable structures. For instance, the model predicts that the SL1 domain of HIV-1 RNA can form two different dimer structures with similar stabilities. The prediction is consistent with experimental observation. In addition, the model predicts two different binding sites for hTR dimerization: One binding site has been experimentally proposed, and the other structure, which has a higher stability, is structurally feasible and needs further experimental validation.

Exploring the electrostatic energy landscape for tetraloop-receptor docking

It has long been appreciated that Mg(2+) is essential for the stabilization of RNA tertiary structure. However, the problem of quantitative prediction for the ion effect in tertiary structure folding remains. By using the virtual bond RNA folding model (Vfold) to generate RNA conformations and the newly improved tightly bound ion model (TBI) to treat ion-RNA interactions, we investigate Mg(2+)-facilitated tetraloop-receptor docking. For the specific construct of the tetraloop-receptor system, the theoretical analysis shows that the Mg(2+)-induced stabilizing force for the docked state is predominantly entropic and the major contribution comes from the entropy of the diffusive ions. Furthermore, our results show that Mg(2+) ions promote tetraloop-receptor docking mainly through the entropy of the diffusive ions. The theoretical prediction agrees with experimental analysis. The method developed in this paper, which combines the theory for the (Mg(2+)) ion effects in RNA folding and RNA conformational sampling, may provide a useful framework for studying the ion effect in the folding of more complex RNA structures.

Three-dimensional RNA structure of the major HIV-1 packaging signal region

HIV-1 genomic RNA has a noncoding 5′ region containing sequential conserved structural motifs that control many parts of the life cycle. Very limited data exist on their three-dimensional (3D) conformation and, hence, how they work structurally. To assemble a working model, we experimentally reassessed secondary structure elements of a 240-nt region and used single-molecule distances, derived from fluorescence resonance energy transfer, between defined locations in these elements as restraints to drive folding of the secondary structure into a 3D model with an estimated resolution below 10 Å. The folded 3D model satisfying the data is consensual with short nuclear-magnetic-resonance-solved regions and reveals previously unpredicted motifs, offering insight into earlier functional assays. It is a 3D representation of this entire region, with implications for RNA dimerization and protein binding during regulatory steps. The structural information of this highly conserved region of the virus has the potential to reveal promising therapeutic targets.

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The 2D structure of the HIV-1 5′ UTR RNA has been elucidated in a monomerized form

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The low-resolution 3D structure has been determined by FRET and simulated annealing

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Modeling has revealed an unpredicted kink turn