RNA structural motifs: building blocks of a modular biomolecule

RNATACs: Multispecific small molecules targeting RNA by induced proximity

RNA-targeting small molecules (rSMs) have become an attractive modality to tackle traditionally undruggable proteins and expand the druggable space. Among many innovative concepts, RNA-targeting chimeras (RNATACs) represent a new class of multispecific, induced proximity small molecules that act by chemically bringing RNA targets into proximity with an endogenous RNA effector, such as a ribonuclease (RNase). Depending on the RNA effector, RNATACs can alter the stability, localization, translation, or splicing of the target RNA. Although still in its infancy, this new modality has the potential for broad applications in the future to treat diseases with high unmet need. In this review, we discuss potential advantages of RNATACs, recent progress in the field, and challenges to this cutting-edge technology.

Self-assembling biomolecules for biosensor applications

Molecular self-assembly has received considerable attention in biomedical fields as a simple and effective method for developing biomolecular nanostructures. Self-assembled nanostructures can exhibit high binding affinity and selectivity by displaying multiple ligands/receptors on their surface. In addition, the use of supramolecular structure change upon binding is an intriguing approach to generate binding signal. Therefore, many self-assembled nanostructure-based biosensors have been developed over the past decades, using various biomolecules (e.g., peptides, DNA, RNA, lipids) and their combinations with non-biological substances. In this review, we provide an overview of recent developments in the design and fabrication of self-assembling biomolecules for biosensing. Furthermore, we discuss representative electrochemical biosensing platforms which convert the biochemical reactions of those biomolecules into electrical signals (e.g., voltage, ampere, potential difference, impedance) to contribute to detect targets. This paper also highlights the successful outcomes of self-assembling biomolecules in biosensor applications and discusses the challenges that this promising technology needs to overcome for more widespread use.

The pseudotorsional space of RNA

The characterization of the conformational landscape of the RNA backbone is rather complex due to the ability of RNA to assume a large variety of conformations. These backbone conformations can be depicted by pseudotorsional angles linking RNA backbone atoms, from which Ramachandran-like plots can be built. We explore here different definitions of these pseudotorsional angles, finding that the most accurate ones are the traditional η (eta) and θ (theta) angles, which represent the relative position of RNA backbone atoms P and C4'. We explore the distribution of η - θ in known experimental structures, comparing the pseudotorsional space generated with structures determined exclusively by one experimental technique. We found that the complete picture only appears when combining data from different sources. The maps provide a quite comprehensive representation of the RNA accessible space, which can be used in RNA-structural predictions. Finally, our results highlight that protein interactions lead to significant changes in the population of the η - θ space, pointing toward the role of induced-fit mechanisms in protein-RNA recognition.

A comprehensive survey of long-range tertiary interactions and motifs in non-coding RNA structures

Understanding the 3D structure of RNA is key to understanding RNA function. RNA 3D structure is modular and can be seen as a composition of building blocks of various sizes called tertiary motifs. Currently, long-range motifs formed between distant loops and helical regions are largely less studied than the local motifs determined by the RNA secondary structure. We surveyed long-range tertiary interactions and motifs in a non-redundant set of non-coding RNA 3D structures. A new dataset of annotated LOng-RAnge RNA 3D modules (LORA) was built using an approach that does not rely on the automatic annotations of non-canonical interactions. An original algorithm, ARTEM, was developed for annotation-, sequence- and topology-independent superposition of two arbitrary RNA 3D modules. The proposed methods allowed us to identify and describe the most common long-range RNA tertiary motifs. Along with the prevalent canonical A-minor interactions, a large number of previously undescribed staple interactions were observed. The most frequent long-range motifs were found to belong to three main motif families: planar staples, tilted staples, and helical packing motifs.

RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families

MOTIVATION

The 3D structures of RNA play a critical role in understanding their functionalities. There exist several computational methods to study RNA 3D structures by identifying structural motifs and categorizing them into several motif families based on their structures. Although the number of such motif families is not limited, a few of them are well-studied. Out of these structural motif families, there exist several families that are visually similar or very close in structure, even with different base interactions. Alternatively, some motif families share a set of base interactions but maintain variation in their 3D formations. These similarities among different motif families, if known, can provide a better insight into the RNA 3D structural motifs as well as their characteristic functions in cell biology.

RESULTS

In this work, we proposed a method, RNAMotifComp, that analyzes the instances of well-known structural motif families and establishes a relational graph among them. We also have designed a method to visualize the relational graph where the families are shown as nodes and their similarity information is represented as edges. We validated our discovered correlations of the motif families using RNAMotifContrast. Additionally, we used a basic Naïve Bayes classifier to show the importance of RNAMotifComp. The relational analysis explains the functional analogies of divergent motif families and illustrates the situations where the motifs of disparate families are predicted to be of the same family.

AVAILABILITY AND IMPLEMENTATION

Source code publicly available at https://github.com/ucfcbb/RNAMotifFamilySimilarity.

Conformational dynamics of RNA G4C2 and G2C4 repeat expansions causing ALS/FTD using NMR and molecular dynamics studies

G4C2 and G2C4 repeat expansions in chromosome 9 open reading frame 72 (C9orf72) are the most common cause of genetically defined amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), or c9ALS/FTD. The gene is bidirectionally transcribed, producing G4C2 repeats [r(G4C2)exp] and G2C4 repeats [r(G2C4)exp]. The c9ALS/FTD repeat expansions are highly structured, and structural studies showed that r(G4C2)exp predominantly folds into a hairpin with a periodic array of 1 × 1 G/G internal loops and a G-quadruplex. A small molecule probe revealed that r(G4C2)exp also adopts a hairpin structure with 2 × 2 GG/GG internal loops. We studied the conformational dynamics adopted by 2 × 2 GG/GG loops using temperature replica exchange molecular dynamics (T-REMD) and further characterized the structure and underlying dynamics using traditional 2D NMR techniques. These studies showed that the loop's closing base pairs influence both structure and dynamics, particularly the configuration adopted around the glycosidic bond. Interestingly, r(G2C4) repeats, which fold into an array of 2 × 2 CC/CC internal loops, are not as dynamic. Collectively, these studies emphasize the unique sensitivity of r(G4C2)exp to small changes in stacking interactions, which is not observed in r(G2C4)exp, providing important considerations for further principles in structure-based drug design.

Fragment-Based Approaches to Identify RNA Binders

Although fragment-based drug discovery (FBDD) has been successfully implemented and well-explored for protein targets, its feasibility for RNA targets is emerging. Despite the challenges associated with the selective targeting of RNA, efforts to integrate known methods of RNA binder discovery with fragment-based approaches have been fruitful, as a few bioactive ligands have been identified. Here, we review various fragment-based approaches implemented for RNA targets and provide insights into experimental design and outcomes to guide future work in the area. Indeed, investigations surrounding the molecular recognition of RNA by fragments address rather important questions such as the limits of molecular weight that confer selective binding and the physicochemical properties favorable for RNA binding and bioactivity.

Context-dependence of T-loop Mediated Long-range RNA Tertiary Interactions

The architecture and folding of complex RNAs is governed by a limited set of highly recurrent structural motifs that form long-range tertiary interactions. One of these motifs is the T-loop, which was first identified in tRNA but is broadly distributed across biological RNAs. While the T-loop has been examined in detail in different biological contexts, the various receptors that it interacts with are not as well defined. In this study, we use a cell-based genetic screen in concert with bioinformatic analysis to examine three different, but related, T-loop receptor motifs found in the flavin mononucleotide (FMN) and cobalamin (Cbl) riboswitches. As a host for different T-loop receptors, we employed the env8 class-II Cbl riboswitch, an RNA that uses two T-loop motifs for both folding and supporting the ligand binding pocket. A set of libraries was created in which select nucleotides that participate in the T-loop/T-loop receptor (TL/TLR) interaction were fully randomized. Library members were screened for their ability to support Cbl-dependent expression of a reporter gene. While T-loops appear to be variable in sequence, we find that the functional sequence space is more restricted in the Cbl riboswitch, suggesting that TL/TLR interactions are context dependent. Our data reveal clear sequence signatures for the different types of receptor motifs that align with phylogenic analysis of these motifs in the FMN and Cbl riboswitches. Finally, our data suggest the functional contribution of various nucleobase-mediated long-range interactions within the riboswitch subclass of TL/TLR interactions that are distinct from those found in other RNAs.

Problem of Domain/Building Block Preservation in the Evolution of Biological Macromolecules and Evolutionary Computation

Structurally and functionally isolated domains in biological macromolecular evolution, both natural and artificial, are largely similar to "schemata", building blocks (BBs), in evolutionary computation (EC). The problem of preserving in subsequent evolutionary searches the already found domains / BBs is well known and quite relevant in biology as well as in EC. Both biology and EC are seeing parallel and independent development of several approaches to identifying and preserving previously identified domains / BBs. First, we notice the similarity of DNA shuffling methods in synthetic biology and multi-parent recombination algorithms in EC. Furthermore, approaches to computer identification of domains in proteins that are being developed in biology can be aligned with BB identification methods in EC. Finally, approaches to chimeric protein libraries optimization in biology can be compared to evolutionary search methods based on probabilistic models in EC. We propose to validate the prospects of mutual exchange of ideas and transfer of algorithms and approaches between evolutionary systems biology and EC in these three principal directions. A crucial aim of this transfer is the design of new advanced experimental techniques capable of solving more complex problems of in vitro evolution.

Automated 3D Design and Evaluation of RNA Nanostructures with RNAMake

Despite growing interest in applying RNA's unique structural characteristics to solve diverse biotechnology and nanotechnology problems, there are few computational tools for targeted tertiary design. As a result, RNA 3D design is traditionally slow, resource-consuming, and dependent on expert modeling. In this chapter, we discuss our recently developed software package: RNAMake, a set of applications capable of designing RNA tertiary structures to solve various relevant nanotechnology problems and provide basic thermodynamic calculations for the generated designs. We provide in-depth examples and instructions for designing example RNA nanostructures such as minimal RNA sequences containing a single tertiary contact, generating RNAs that stabilize small-molecule ligands, and building tethers that link ribosomal subunits together. We also highlight the addition of a new Monte Carlo design algorithm and the ability to estimate the thermodynamic contribution of helical elements in RNA 3D structures.

Computational prediction of disease related lncRNAs using machine learning

Long non-coding RNAs (lncRNAs), which were once considered as transcriptional noise, are now in the limelight of current research. LncRNAs play a major role in regulating various biological processes such as imprinting, cell differentiation, and splicing. The mutations of lncRNAs are involved in various complex diseases. Identifying lncRNA-disease associations has gained a lot of attention as predicting it efficiently will lead towards better disease treatment. In this study, we have developed a machine learning model that predicts disease-related lncRNAs by combining sequence and structure-based features. The features were trained on SVM and Random Forest classifiers. We have compared our method with the state-of-the-art and obtained the highest F1 score of 76% on SVM classifier. Moreover, this study has overcome two serious limitations of the reported method which are lack of redundancy checking and implementation of oversampling for balancing the positive and negative class. Our method has achieved improved performance among machine learning models reported for lncRNA-disease associations. Combining multiple features together specifically lncRNAs sequence mutation has a significant contribution to the disease related lncRNA prediction.

Modified Nucleotides for Chemical and Enzymatic Synthesis of Therapeutic RNA

In recent years, RNA has emerged as a medium with a broad spectrum of therapeutic potential, however, for years, a group of short RNA fragments was studied and considered therapeutic molecules. In nature, RNA plays both functions, with coding and non-coding potential. For RNA, like any other therapeutic, to be used clinically, certain barriers must be crossed. Among them, there are biocompatibility, relatively low toxicity, bioavailability, increased stability, target efficiency and low off-target effects. In the case of RNA, most of these obstacles can be overcome by incorporating modified nucleotides into its structure. This may be achieved by both, in vitro and in vivo biosynthetic methods, as well as chemical synthesis. Some advantages and disadvantages of each approach are summarized here. The wide range of nucleotide analogues has been tested for their utility as monomers for RNA synthesis. Many of them have been successfully implemented, and a lot of pre-clinical and clinical studies involving modified RNA have been carried out. Some of these medications have already been introduced into clinics. After the huge success of RNA-based vaccines that were introduced into widespread use in 2020, and the introduction to the market of some RNA-based drugs, RNA therapeutics containing modified nucleotides appear to be the future of medicine.

Biomolecule-mimetic nanomaterials for photothermal and photodynamic therapy of cancers: Bridging nanobiotechnology and biomedicine

Nanomaterial-based phototherapy has become an important research direction for cancer therapy, but it still to face some obstacles, such as the toxic side effects and low target specificity. The biomimetic synthesis of nanomaterials using biomolecules is a potential strategy to improve photothermal therapy (PTT) and photodynamic therapy (PDT) techniques due to their endowed biocompatibility, degradability, low toxicity, and specific targeting. This review presents recent advances in the biomolecule-mimetic synthesis of functional nanomaterials for PTT and PDT of cancers. First, we introduce four biomimetic synthesis methods via some case studies and discuss the advantages of each method. Then, we introduce the synthesis of nanomaterials using some biomolecules such as DNA, RNA, protein, peptide, polydopamine, and others, and discuss in detail how to regulate the structure and functions of the obtained biomimetic nanomaterials. Finally, potential applications of biomimetic nanomaterials for both PTT and PDT of cancers are demonstrated and discussed. We believe that this work is valuable for readers to understand the mechanisms of biomimetic synthesis and nanomaterial-based phototherapy techniques, and will contribute to bridging nanotechnology and biomedicine to realize novel highly effective cancer therapies.

Riboswitch-mediated regulation of riboflavin biosynthesis genes in prokaryotes

Prokaryotic organisms frequently use riboswitches to quantify intracellular metabolite concentration via high-affinity metabolite receptors. Riboswitches possess a metabolite-sensing system that controls gene regulation in a cis-acting fashion at the initiation of transcriptional/translational level by binding with a specific metabolite and controlling various biochemical pathways. Riboswitch binds with flavin mononucleotide (FMN), a phosphorylated form of riboflavin and controls gene expression involved in riboflavin biosynthesis and transport pathway. The first step of the riboflavin biosynthesis pathway is initiated by the conversion of guanine nucleotide triphosphate (GTP), which is an intermediate of the purine biosynthesis pathway. An alternative pentose phosphate pathway of riboflavin biosynthesis includes the enzymatic conversion of ribulose-5-phosphate into 3, 4 dihydroxy-2-butanone-4-phosphates by DHBP synthase. The product of ribAB interferes with both GTP cyclohydrolase II as well as DHBP synthase activities, which catalyze the cleavage of GTP and converts DHBP Ribu5P in the initial steps of both riboflavin biosynthesis branches. Riboswitches are located in the 5' untranslated region (5' UTR) of messenger RNAs and contain an aptamer domain (highly conserved in sequence) where metabolite binding leads to a conformational change in an aptamer domain, which modulate the regulation of gene expression located on bacterial mRNA. In this review, we focus on how riboswitch regulates the riboflavin biosynthesis pathway in Bacillus subtilis and Lactobacillus plantarum.

RNA-As-Graphs Motif Atlas—Dual Graph Library of RNA Modules and Viral Frameshifting-Element Applications

RNA motif classification is important for understanding structure/function connections and building phylogenetic relationships. Using our coarse-grained RNA-As-Graphs (RAG) representations, we identify recurrent dual graph motifs in experimentally solved RNA structures based on an improved search algorithm that finds and ranks independent RNA substructures. Our expanded list of 183 existing dual graph motifs reveals five common motifs found in transfer RNA, riboswitch, and ribosomal 5S RNA components. Moreover, we identify three motifs for available viral frameshifting RNA elements, suggesting a correlation between viral structural complexity and frameshifting efficiency. We further partition the RNA substructures into 1844 distinct submotifs, with pseudoknots and junctions retained intact. Common modules are internal loops and three-way junctions, and three submotifs are associated with riboswitches that bind nucleotides, ions, and signaling molecules. Together, our library of existing RNA motifs and submotifs adds to the growing universe of RNA modules, and provides a resource of structures and substructures for novel RNA design.

Box-shaped ribozyme octamer formed by face-to-face dimerization of a pair of square-shaped ribozyme tetramers

Naturally occurring ribozymes with defined three-dimensional (3D) structures serve as promising platforms for the design and construction of artificial RNA nanostructures. We constructed a hexameric ribozyme nanostructure by face-to-face dimerization of a pair of triangular ribozyme trimers, unit RNAs of which were derived from the Tetrahymena group I ribozyme. In this study, we have expanded the dimerization strategy to a square-shaped ribozyme tetramer by introducing four pillar units. The resulting box-shaped nanostructures, which contained eight ribozyme units, can be assembled from either four or two components of their unit RNAs.

Advances in nanotechnology-based platforms for survivin-targeted drug discovery

INTRODUCTION

Due to its unique functional impact on multiple cancer cell circuits including proliferation, apoptosis, tumor dissemination, DNA damage repair and immune response, the inhibitor of apoptosis protein (IAP) survivin has gained high interest as a molecular target and a multitude of therapeutics were developed to interfere with survivin expression and functionality. First clinical evaluations of these therapeutics, however, were disappointing highlighting the need to develop advanced delivery systems of survivin-targeting molecules to increase stability, bioavailability as well as the selective guidance to tumor tissue.

AREAS COVERED

: This review focuses on advancements in nanocarriers to molecularly target survivin in human malignancies. A plethora of nanoparticle platforms, including liposomes, polymeric systems, dendrimers, inorganic nanocarriers, RNA/DNA nanotechnology and exosomes are discussed in the background of survivin-tailored RNA interference, small molecule inhibitors, dominant negative mutants or survivin vaccination or combined modality treatment with chemotherapeutic drugs and photo- dynamic/photothermal strategies.

EXPERT OPINION

Novel therapeutic approaches include the use of biocompatible nanoformulations carrying gene silencing or drug molecules to directly or indirectly target proteins, allow for a more precise and controlled delivery of survivin therapeutics. Moreover, surface modification of these nanocarriers may result in a tumor entity specific delivery. Therefore, nanomedicine exploiting survivin-tailored strategies in a multimodal background is considered the way forwaerd to enhance the development of future personalized medicine.

Overview of Methods for Large-Scale RNA Synthesis

In recent years, it has become clear that RNA molecules are involved in almost all vital cellular processes and pathogenesis of human disorders. The functional diversity of RNA comes from its structural richness. Although composed of only four nucleotides, RNA molecules present a plethora of secondary and tertiary structures critical for intra and intermolecular contacts with other RNAs and ligands (proteins, small metabolites, etc.). In order to fully understand RNA function it is necessary to define its spatial structure. Crystallography, nuclear magnetic resonance and cryogenic electron microscopy have demonstrated considerable success in determining the structures of biologically important RNA molecules. However, these powerful methods require large amounts of sample. Despite their limitations, chemical synthesis and in vitro transcription are usually employed to obtain milligram quantities of RNA for structural studies, delivering simple and effective methods for large-scale production of homogenous samples. The aim of this paper is to provide an overview of methods for large-scale RNA synthesis with emphasis on chemical synthesis and in vitro transcription. We also present our own results of testing the efficiency of these approaches in order to adapt the material acquisition strategy depending on the desired RNA construct.

Heuristic algorithms in evolutionary computation and modular organization of biological macromolecules: Applications to in vitro evolution

Evolutionary computing (EC) is an area of computer sciences and applied mathematics covering heuristic optimization algorithms inspired by evolution in Nature. EC extensively study all the variety of methods which were originally based on the principles of selectionism. As a result, many new algorithms and approaches, significantly more efficient than classical selectionist schemes, were found. This is especially true for some families of special problems. There are strong arguments to believe that EC approaches are quite suitable for modeling and numerical analysis of those methods of synthetic biology and biotechnology that are known as in vitro evolution. Therefore, it is natural to expect that the new algorithms and approaches developed in EC can be effectively applied in experiments on the directed evolution of biological macromolecules. According to the John Holland's Schema theorem, the effective evolutionary search in genetic algorithms (GA) is provided by identifying short schemata of high fitness which in the further search recombine into the larger building blocks (BBs) with higher and higher fitness. The multimodularity of functional biological macromolecules and the preservation of already found modules in the evolutionary search have a clear analogy with the BBs in EC. It seems reasonable to try to transfer and introduce the methods of EC, preserving BBs and essentially accelerating the search, into experiments on in vitro evolution. We extend the key instrument of the Holland's theory, the Royal Roads fitness function, to problems of the in vitro evolution (Biological Royal Staircase, BioRS, functions). The specific version of BioRS developed in this publication arises from the realities of experimental evolutionary search for (DNA-) RNA-devices (aptazymes). Our numerical tests showed that for problems with the BioRS functions, simple heuristic algorithms, which turned out to be very effective for preserving BBs in GA, can be very effective in in vitro evolution approaches. We are convinced that such algorithms can be implemented in modern methods of in vitro evolution to achieve significant savings in time and resources and a significant increase in the efficiency of evolutionary search.

Cooperativity and Interdependency between RNA Structure and RNA-RNA Interactions

Complex RNA–RNA interactions are increasingly known to play key roles in numerous biological processes from gene expression control to ribonucleoprotein granule formation. By contrast, the nature of these interactions and characteristics of their interfaces, especially those that involve partially or wholly structured RNAs, remain elusive. Herein, we discuss different modalities of RNA–RNA interactions with an emphasis on those that depend on secondary, tertiary, or quaternary structure. We dissect recently structurally elucidated RNA–RNA complexes including RNA triplexes, riboswitches, ribozymes, and reverse transcription complexes. These analyses highlight a reciprocal relationship that intimately links RNA structure formation with RNA–RNA interactions. The interactions not only shape and sculpt RNA structures but also are enabled and modulated by the structures they create. Understanding this two-way relationship between RNA structure and interactions provides mechanistic insights into the expanding repertoire of noncoding RNA functions, and may inform the design of novel therapeutics that target RNA structures or interactions.

Importance of Anion-π Interactions in RNA GAAA and GGAG Tetraloops: A Combined MD and QM Study

In this study, we demonstrate that anion−π interactions (an attractive noncovalent force between electron deficient π-systems and anions) are involved in the stabilization of GAAA and GGAG RNA tetraloops. Using the single recognition particle (SRP)–RNA complexes as a case of study, we combined molecular dynamics (MD) and quantum mechanics (QM) calculations to shed light on the structural influence of phosphate–G anion−π interactions and hydrogen bonds (HBs) involving K⁺/Mg²⁺ water clusters. In addition, the RNA assemblies herein were further characterized by means of the “atoms in molecules” (AIM) and noncovalent interactions plot (NCIplot) methodologies. We believe the results derived from this study might be important in the fields of chemical biology (RNA folding and engineering) and supramolecular chemistry (anion−π interactions) as well as to further expand the current knowledge regarding RNA structural motifs.

Conservation in the Iron Responsive Element Family

Iron responsive elements (IREs) are mRNA stem-loop targets for translational control by the two iron regulatory proteins IRP1 and IRP2. They are found in the untranslated regions (UTRs) of genes that code for proteins involved in iron metabolism. There are ten “classic” IRE types that define the conserved secondary and tertiary structure elements necessary for proper IRP binding, and there are 83 published “IRE-like” sequences, most of which depart from the established IRE model. Here are structurally-guided discussions regarding the essential features of an IRE and what is important for IRE family membership.

Aptamers isolated against mosquito-borne pathogens

Mosquito-borne diseases are a major threat to public health. The shortcomings of diagnostic tools, especially those that are antibody-based, have been blamed in part for the rising annual morbidity and mortality caused by these diseases. Antibodies harbor a number of disadvantages that can be clearly addressed by aptamers as the more promising molecular recognition elements. Aptamers are defined as single-stranded DNA or RNA oligonucleotides generated by SELEX that exhibit high binding affinity and specificity against a wide variety of target molecules based on their unique structural conformations. A number of aptamers were developed against mosquito-borne pathogens such as Dengue virus, Zika virus, Chikungunya virus, Plasmodium parasite, Francisella tularensis, Japanese encephalitis virus, Venezuelan equine encephalitis virus, Rift Valley fever virus and Yellow fever virus. Intrigued by these achievements, we carry out a comprehensive overview of the aptamers developed against these mosquito-borne infectious agents. Characteristics of the aptamers and their roles in diagnostic, therapeutic as well as other applications are emphasized.

Annotation of the local context of the RNA secondary structure improves the classification and prediction of A-minors

Non-coding RNAs play a crucial role in various cellular processes in living organisms, and RNA functions heavily depend on molecule structures composed of stems, loops, and various tertiary motifs. Among those, the most frequent are A-minor interactions, which are often involved in the formation of more complex motifs such as kink-turns and pseudoknots. We present a novel classification of A-minors in terms of RNA secondary structure where each nucleotide of an A-minor is attributed to the stem or loop, and each pair of nucleotides is attributed to their relative position within the secondary structure. By analyzing classes of A-minors in known RNA structures, we found that the largest classes are mostly homogeneous and preferably localize with known A-minor co-motifs, e.g. tetraloop-tetraloop receptor and coaxial stacking. Detailed analysis of local A-minors within internal loops revealed a novel recurrent RNA tertiary motif, the across-bulged motif. Interestingly, the motif resembles the previously known GAAA/11nt motif but with the local adenines performing the role of the GAAA-tetraloop. By using machine learning, we show that particular classes of local A-minors can be predicted from sequence and secondary structure. The proposed classification is the first step toward automatic annotation of not only A-minors and their co-motifs but various types of RNA tertiary motifs as well.

Affinity and Structural Analysis of the U1A RNA Recognition Motif with Engineered Methionines to Improve Experimental Phasing

RNA plays a central role in all organisms and can fold into complex structures to orchestrate function. Visualization of such structures often requires crystallization, which can be a bottleneck in the structure-determination process. To promote crystallization, an RNA-recognition motif (RRM) of the U1A spliceosomal protein has been co-opted as a crystallization module. Specifically, the U1-snRNA hairpin II (hpII) single-stranded loop recognized by U1A can be transplanted into an RNA target to promote crystal contacts and to attain phase information via molecular replacement or anomalous diffraction methods using selenomethionine. Herein, we produced the F37M/F77M mutant of U1A to augment the phasing capability of this powerful crystallization module. Selenomethionine-substituted U1A(F37M/F77M) retains high affinity for hpII (K _D of 59.7 ± 11.4 nM). The 2.20 Å resolution crystal structure reveals that the mutated sidechains make new S-π interactions in the hydrophobic core and are useful for single-wavelength anomalous diffraction. Crystals were also attained of U1A(F37M/F77M) in complex with a bacterial preQ₁-II riboswitch. The F34M/F37M/F77M mutant was introduced similarly into a lab-evolved U1A variant (TBP6.9) that recognizes the internal bulged loop of HIV-1 TAR RNA. We envision that this short RNA sequence can be placed into non-essential duplex regions to promote crystallization and phasing of target RNAs. We show that selenomethionine-substituted TBP6.9(F34M/F37M/F77M) binds a TAR variant wherein the apical loop was replaced with a GNRA tetraloop (K _D of 69.8 ± 2.9 nM), laying the groundwork for use of TBP6.9(F34M/F37M/F77M) as a crystallization module. These new tools are available to the research community.

Incorporating a Thiophosphate Modification into a Common RNA Tetraloop Motif Causes an Unanticipated Stability Boost

GNRA (N = A, C, G, or U; R = A or G) tetraloops are common RNA secondary structural motifs and feature a phosphate stacked atop a nucleobase. The rRNA sarcin/ricin loop (SRL) is capped by GApGA, and the phosphate p stacks on G. We recently found that regiospecific incorporation of a single dithiophosphate (PS2) but not a monothiophosphate (PSO) instead of phosphate in the backbone of RNA aptamers dramatically increases the binding affinity for their targets. In the RNA:thrombin complex, the key contribution to the 1000-fold tighter binding stems from an edge-on contact between PS2 and a phenylalanine ring. Here we investigated the consequences of replacing the SRL phosphate engaged in a face-on interaction with guanine with either PS2 or PSO for stability. We found that PS2···G and Rp-PSO···G contacts stabilize modified SRLs compared to the parent loop to unexpected levels: up to 6.3 °C in melting temperature T_m and -4.7 kcal/mol in ΔΔG°. Crystal structures demonstrate that the vertical distance to guanine for the closest sulfur is just 0.05 Å longer on average compared to that of oxygen despite the larger van der Waals radius of the former (1.80 Å for S vs 1.52 Å for O). The higher stability is enthalpy-based, and the negative charge as assessed by a neutral methylphosphonate modification plays only a minor role. Quantum mechanical/molecular mechanical calculations are supportive of favorable dispersion attraction interactions by sulfur making the dominant contribution. A stacking interaction between phosphate and guanine (SRL) or uracil (U-turn) is also found in newly classified RNA tetraloop families besides GNRA.

Design of small molecules targeting RNA structure from sequence

The design and discovery of small molecule medicines has largely been focused on a small number of druggable protein families. A new paradigm is emerging, however, in which small molecules exert a biological effect by interacting with RNA, both to study human disease biology and provide lead therapeutic modalities. Due to this potential for expanding target pipelines and treating a larger number of human diseases, robust platforms for the rational design and optimization of small molecules interacting with RNAs (SMIRNAs) are in high demand. This review highlights three major pillars in this area. First, the transcriptome-wide identification and validation of structured RNA elements, or motifs, within disease-causing RNAs directly from sequence is presented. Second, we provide an overview of high-throughput screening approaches to identify SMIRNAs as well as discuss the lead identification strategy, Inforna, which decodes the three-dimensional (3D) conformation of RNA motifs with small molecule binding partners, directly from sequence. An emphasis is placed on target validation methods to study the causality between modulating the RNA motif in vitro and the phenotypic outcome in cells. Third, emergent modalities that convert occupancy-driven mode of action SMIRNAs into event-driven small molecule chemical probes, such as RNA cleavers and degraders, are presented. Finally, the future of the small molecule RNA therapeutics field is discussed, as well as hurdles to overcome to develop potent and selective RNA-centric chemical probes.

On the Way to Understanding the Interplay between the RNA Structure and Functions in Cells: A Genome-Wide Perspective

RNAs adopt specific structures in order to perform their biological activities. The structure of RNA is an important layer of gene expression regulation, and can impact a plethora of cellular processes, starting with transcription, RNA processing, and translation, and ending with RNA turnover. The development of high-throughput technologies has enabled a deeper insight into the sophisticated interplay between the structure of the cellular transcriptome and the living cells environment. In this review, we present the current view on the RNA structure in vivo resulting from the most recent transcriptome-wide studies in different organisms, including mammalians, yeast, plants, and bacteria. We focus on the relationship between the mRNA structure and translation, mRNA stability and degradation, protein binding, and RNA posttranscriptional modifications.

[Non-coding Natural Antisense RNA: Mechanisms of Action in the Regulation of Target Gene Expression and Its Clinical Implications]

Recent advances in high-throughput technologies have revealed that 75% of the human genome is transcribed to RNA, whereas only 3% of transcripts are translated into proteins. Consequently, many long non-coding RNAs (lncRNAs) have been identified, which has improved our understanding of the complexity of biological processes. LncRNAs comprise multiple classes of RNA transcripts that regulate the transcription, stability and translation of protein-coding genes in a genome. Natural antisense transcripts (NATs) form one such class, and the GENCODE v30 catalog contains 16193 lncRNA loci, of which 5611 are antisense loci. This review outlines our emerging understanding of lncRNAs, with a particular focus on how lncRNAs regulate gene expression using interferon-α1 (IFN-α1) mRNA and its antisense partner IFN-α1 antisense (as)RNA as an example. We have identified and characterized the asRNA that determines post-transcriptional IFN-α1 mRNA levels. IFN-α1 asRNA stabilizes IFN-α1 mRNA by cytoplasmic sense-antisense duplex formation, which may enhance the accessibility of an RNA stabilizer protein or decrease the affinity of an RNA decay factor for the RNA. IFN-α1 asRNA can also act as competing molecules in the competing endogenous (ce)RNA network with other members of the IFNA multigene family mRNAs/asRNAs, and other cellular mRNA transcripts. Furthermore, antisense oligoribonucleotides representing functional domains of IFN-α1 asRNA inhibit influenza virus proliferation in the respiratory tract of virus-infected animals. Thus, these findings support, at least in part, the rationale that dissecting the activity of NAT on gene expression regulation promises to reveal previously unanticipated biology, with potential to provide new therapeutic approaches to diseases.

Intrinsic Regulatory Role of RNA Structural Arrangement in Alternative Splicing Control

Alternative splicing is a highly sophisticated process, playing a significant role in posttranscriptional gene expression and underlying the diversity and complexity of organisms. Its regulation is multilayered, including an intrinsic role of RNA structural arrangement which undergoes time- and tissue-specific alterations. In this review, we describe the principles of RNA structural arrangement and briefly decipher its cis- and trans-acting cellular modulators which serve as crucial determinants of biological functionality of the RNA structure. Subsequently, we engage in a discussion about the RNA structure-mediated mechanisms of alternative splicing regulation. On one hand, the impairment of formation of optimal RNA structures may have critical consequences for the splicing outcome and further contribute to understanding the pathomechanism of severe disorders. On the other hand, the structural aspects of RNA became significant features taken into consideration in the endeavor of finding potential therapeutic treatments. Both aspects have been addressed by us emphasizing the importance of ongoing studies in both fields.

HiPR: High-throughput probabilistic RNA structure inference

Recent high-throughput structure-sensitive genome-wide sequencing-based assays have enabled large-scale studies of RNA structure, and robust transcriptome-wide computational prediction of individual RNA structures across RNA classes from these assays has potential to further improve the prediction accuracy. Here, we describe HiPR, a novel method for RNA structure prediction at single-nucleotide resolution that combines high-throughput structure probing data (DMS-seq, DMS-MaPseq) with a novel probabilistic folding algorithm. On validation data spanning a variety of RNA classes, HiPR often increases accuracy for predicting RNA structures, giving researchers new tools to study RNA structure.

Crystal structures of an unmodified bacterial tRNA reveal intrinsic structural flexibility and plasticity as general properties of unbound tRNAs

Ubiquitous across all domains of life, tRNAs constitute an essential component of cellular physiology, carry out an indispensable role in protein synthesis, and have been historically the subject of a wide range of biochemical and biophysical studies as prototypical folded RNA molecules. Although conformational flexibility is a well-established characteristic of tRNA structure, it is typically regarded as an adaptive property exhibited in response to an inducing event, such as the binding of a tRNA synthetase or the accommodation of an aminoacyl-tRNA into the ribosome. In this study, we present crystallographic data of a tRNA molecule to expand on this paradigm by showing that structural flexibility and plasticity are intrinsic properties of tRNAs, apparent even in the absence of other factors. Based on two closely related conformations observed within the same crystal, we posit that unbound tRNAs by themselves are flexible and dynamic molecules. Furthermore, we demonstrate that the formation of the T-loop conformation by the tRNA TΨC stem-loop, a well-characterized and classic RNA structural motif, is possible even in the absence of important interactions observed in fully folded tRNAs.

Truncated tetrahedral RNA nanostructures exhibit enhanced features for delivery of RNAi substrates

Using RNA as a material for nanoparticle construction provides control over particle size and shape at the nano-scale. RNA nano-architectures have shown promise as delivery vehicles for RNA interference (RNAi) substrates, allowing multiple functional entities to be combined on a single particle in a programmable fashion. Rather than employing a completely bottom-up approach to scaffold design, here multiple copies of an existing synthetic supramolecular RNA nano-architecture serve as building blocks along with additional motifs for the design of a novel truncated tetrahedral RNA scaffold, demonstrating that rationally designed RNA assemblies can themselves serve as modular pieces in the construction of larger rationally designed structures. The resulting tetrahedral scaffold displays enhanced characteristics for RNAi-substrate delivery in comparison to similar RNA-based scaffolds, as evidenced by its increased functional capacity, increased cellular uptake and ultimately an increased RNAi efficacy of its adorned Dicer substrate siRNAs. The unique truncated tetrahedral shape of the nanoparticle core appears to contribute to this particle's enhanced function, indicating the physical characteristics of RNA scaffolds merit significant consideration when designing platforms for delivery of functional RNAs via RNA nanoparticles.

RNAdt: An online tutorial and data portal for the RNA structurome era

RNA is not only a passive transporter of genetic information, but also a pivotal player in all domains of life. RNA can regulate gene expression because of its involvement in transcription, mRNA modification and processing, and translation. RNA also possesses other intricate functions such as catalysis, ligand sensing, interaction with biomolecules, response to environment stresses, and information storage. The primary structure of RNA is single stranded, but it always folds into complex secondary and tertiary structures owing to base pairing and effects from the cellular environment. The importance of structure has been increasingly recognized in understanding the myriad functions of RNA. After decades of development, there is a wide range of RNA structure probing techniques. The marriage between structure probing and high-throughput sequencing (HTS) especially enables the measurement of RNA structure on a transcriptomic scale, advancing the advent of the RNA structurome era. Dozens of HTS-associated RNA structure probing methods have been published, so it is urgent to provide a user-friendly and easy-to-use resource for users who are perplexed by selecting the most suitable method for their experiments. Motivated by this demand, we collected currently available HTS-associated RNA structure probing methods and then developed RNAdt (freely accessible at http://www.zhounan.org/rnadt). RNAdt can be used as a web-based tutorial to learn fundamental knowledge of HTS-associated RNA structure probing methods. RNAdt can also be used as a data portal to access HTS data sets from previous RNA structurome studies. At the end of this work, we also provided perspectives on future development of RNA structure probing methods. Our study is expected to facilitate RNA structure probing and ultimately elucidate the connection between RNA structure and biological functions.

Identification of Structural Motifs Using Networks of Hydrogen-Bonded Base Interactions in RNA Crystallographic Structures

RNA structural motifs can be identified using methods that analyze base–base interactions and the conformation of a structure’s backbone; however, these approaches do not necessarily take into consideration the hydrogen bonds that connect the bases or the networks of inter-connected hydrogen-bonded bases that are found in RNA structures. Large clusters of RNA bases that are tightly inter-connected by a network of hydrogen bonds are expected to be stable and relatively rigid substructures. Such base arrangements could therefore be present as structural motifs in RNA structures, especially when there is a requirement for a highly stable support platform or substructure to ensure the correct folding and spatial maintenance of functional sites that partake in catalysis or binding interactions. In order to test this hypothesis, we conducted a search in available RNA crystallographic structures in the Protein Data Bank database using queries that searched for profiles of bases inter-connected by hydrogen bonds. This method of searching does not require to have prior knowledge of the arrangement being searched. Our search results identified two clusters of six bases that are inter-connected by a network of hydrogen bonds. These arrangements of base sextuples have never been previously reported, thus making this the first report that proposes them as novel RNA tertiary motifs.

Tuning the size, shape and structure of RNA nanoparticles for favorable cancer targeting and immunostimulation

The past decade has shown exponential growth in the field of RNA nanotechnology. The rapid advances of using RNA nanoparticles for biomedical applications, especially targeted cancer therapy, suggest its potential as a new generation of drug. After the first milestone of small molecule drugs and the second milestone of antibody drugs, it was predicted that RNA drugs, either RNA itself or chemicals/ligands that target RNA, will be the third milestone in drug development. Thus, a comprehensive assessment of the current therapeutic RNA nanoparticles is urgently needed to meet the drug evaluation criteria. Specifically, the pharmacological and immunological profiles of RNA nanoparticles need to be systematically studied to provide insights in rational design of RNA-based therapeutics. By virtue of its programmability and biocompatibility, RNA molecules can be designed to construct sophisticated nanoparticles with versatile functions/applications and highly tunable physicochemical properties. This intrinsic characteristic allows the systemic study of the effects of various properties of RNA nanoparticles on their in vivo behaviors such as cancer targeting and immune responses. This review will focus on the recent progress of RNA nanoparticles in cancer targeting, and summarize the effects of common physicochemical properties such as size and shape on the RNA nanoparticles' biodistribution and immunostimulation profiles. This article is categorized under: Biology-Inspired Nanomaterials > Nucleic Acid-Based Structures Diagnostic Tools > in vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

In silico survey of the central conserved regions in viroids of the Pospiviroidae family for conserved asymmetric loop structures

Viroids are the smallest replicative pathogens, consisting of RNA circles (∼300 nucleotides) that require host machinery to replicate. Structural RNA elements recruit these host factors. Currently, many of these structural elements and the nature of their interactions are unknown. All Pospiviroidae have homology in the central conserved region (CCR). The CCR of potato spindle tuber viroid (PSTVd) contains a sarcin/ricin domain (SRD), the only viroid structural element with an unequivocal replication role. We assumed that every member of this family uses this region to recruit host factors, and that each CCR has an SRD-like asymmetric loop within it. Potential SRD or SRD-like motifs were sought in the CCR of each Pospiviroidae member as follows. Motif location in each CCR was predicted with MUSCLE alignment and Vienna RNAfold. Viroid-specific models of SRD-like motifs were built by superimposing noncanonical base pairs and nucleotides on a model of an SRD. The RNA geometry search engine FR3D was then used to find nucleotide groups close to the geometry suggested by this superimposition. Atomic resolution structures were assembled using the molecular visualization program Chimera, and the stability of each motif was assessed with molecular dynamics (MD). Some models required a protonated cytosine. To be stable within a cell, the pK_a of that cytosine must be shifted up. Constant pH-replica exchange MD analysis showed such a shift in the proposed structures. These data show that every Pospiviroidae member could form a motif that resembles an SRD in its CCR, and imply there could be undiscovered mimics of other RNA domains.

Evidence for ligandable sites in structured RNA throughout the Protein Data Bank

RNA has attracted considerable attention as a target for small molecules. However, methods to identify, study, and characterize suitable RNA targets have lagged behind strategies for protein targets. One approach that has received considerable attention for protein targets has been to utilize computational analysis to investigate ligandable "pockets" on proteins that are amenable to small molecule binding. These studies have shown that selected physical properties of pockets are important parameters that govern the ability of a structure to bind to small molecules. This work describes a similar analysis to study pockets on all RNAs in the Protein Data Bank (PDB). Using parameters such as buriedness, hydrophobicity, volume, and other properties, the set of all RNAs is analyzed and compared to all proteins. Considerable overlap is observed between the properties of pockets on RNAs and proteins. Thus, many RNAs are capable of populating conformations with pockets that are likely suitable for small molecule binding. Further, principal moment of inertia (PMI) calculations reveal that liganded RNAs exist in diverse structural space, much of which overlaps with protein structural space. Taken together, these results suggest that complex folded RNAs adopt unique structures with pockets that may represent viable opportunities for small molecule targeting.

Face-time with TAR: Portraits of an HIV-1 RNA with diverse modes of effector recognition relevant for drug discovery

Small molecules and short peptides that potently and selectively bind RNA are rare, making the molecular structures of these complexes highly exceptional. Accordingly, several recent investigations have provided unprecedented structural insights into how peptides and proteins recognize the HIV-1 transactivation response (TAR) element, a 59-nucleotide-long, noncoding RNA segment in the 5' long terminal repeat region of viral transcripts. Here, we offer an integrated perspective on these advances by describing earlier progress on TAR binding to small molecules, and by drawing parallels to recent successes in the identification of compounds that target the hepatitis C virus internal ribosome entry site (IRES) and the flavin-mononucleotide riboswitch. We relate this work to recent progress that pinpoints specific determinants of TAR recognition by: (i) viral Tat proteins, (ii) an innovative lab-evolved TAR-binding protein, and (iii) an ultrahigh-affinity cyclic peptide. New structural details are used to model the TAR-Tat-super-elongation complex (SEC) that is essential for efficient viral transcription and represents a focal point for antiviral drug design. A key prediction is that the Tat transactivation domain makes modest contacts with the TAR apical loop, whereas its arginine-rich motif spans the entire length of the TAR major groove. This expansive interface has significant implications for drug discovery and design, and it further suggests that future lab-evolved proteins could be deployed to discover steric restriction points that block Tat-mediated recruitment of the host SEC to HIV-1 TAR.

Estimating Strengths of Individual Hydrogen Bonds in RNA Base Pairs: Toward a Consensus between Different Computational Approaches

Noncoding RNA molecules are composed of a large variety of noncanonical base pairs that shape up their functionally competent folded structures. Each base pair is composed of at least two interbase hydrogen bonds (H-bonds). It is expected that the characteristic geometry and stability of different noncanonical base pairs are determined collectively by the properties of these interbase H-bonds. We have studied the ground-state electronic properties [using density functional theory (DFT) and DFT-D3-based methods] of all the 118 normal base pairs and 36 modified base pairs, belonging to 12 different geometric families (cis and trans of WW, WH, HH, WS, HS, and SS) that occur in a nonredundant set of high-resolution RNA crystal structures. Having addressed some of the limitations of the earlier approaches, we provide here a comprehensive compilation of the average energies of different types of interbase H-bonds (E _HB). We have also characterized each interbase H-bond using 13 different parameters that describe its geometry, charge distribution at its bond critical point (BCP), and n → σ*-type charge transfer from filled π orbitals of the H-bond acceptor to the empty antibonding orbital of the H-bond donor. On the basis of the extent of their linear correlation with the H-bonding energy, we have shortlisted five parameters to model linear equations for predicting E _HB values. They are (i) electron density at the BCP: ρ, (ii) its Laplacian: ∇²ρ, (iii) stabilization energy due to n → σ*-type charge transfer: E(2), (iv) donor-hydrogen distance, and (v) hydrogen-acceptor distance. We have performed single variable and multivariable linear regression analysis over the normal base pairs and have modeled sets of linear relationships between these five parameters and E _HB. Performance testing of our model over the set of modified base pairs shows promising results, at least for the moderately strong H-bonds.

Genome-wide discovery of structured noncoding RNAs in bacteria

Background

Structured noncoding RNAs (ncRNAs) play essential roles in many biological processes such as gene regulation, signaling, RNA processing, and protein synthesis. Among the most common groups of ncRNAs in bacteria are riboswitches. These cis-regulatory, metabolite-binding RNAs are present in many species where they regulate various metabolic and signaling pathways. Collectively, there are likely to be hundreds of novel riboswitch classes that remain hidden in the bacterial genomes that have already been sequenced, and potentially thousands of classes distributed among various other species in the biosphere. The vast majority of these undiscovered classes are proposed to be exceedingly rare, and so current bioinformatics search techniques are reaching their limits for differentiating between true riboswitch candidates and false positives.

Results

Herein, we exploit a computational search pipeline that can efficiently identify intergenic regions most likely to encode structured ncRNAs. Application of this method to five bacterial genomes yielded nearly 70 novel genetic elements including 30 novel candidate ncRNA motifs. Among the riboswitch candidates identified is an RNA motif involved in the regulation of thiamin biosynthesis.

Conclusions

Analysis of other genomes will undoubtedly lead to the discovery of many additional novel structured ncRNAs, and provide insight into the range of riboswitches and other kinds of ncRNAs remaining to be discovered in bacteria and archaea.

Electronic supplementary material

The online version of this article (10.1186/s12866-019-1433-7) contains supplementary material, which is available to authorized users.

Ribosome-induced RNA conformational changes in a viral 3'-UTR sense and regulate translation levels

Structured RNA elements, programmed RNA conformational changes, and interactions between different RNA domains underlie many modes of regulating gene expression, mandating studies to understand the foundational principles that govern these phenomena. Exploring the structured 3' untranslated region (UTR) of a viral RNA, we discovered that different contexts of the 3'-UTR confer different abilities to enhance translation of an associated open reading frame. In one context, ribosome-induced conformational changes in a 'sensor' RNA domain affect a separate RNA 'functional' domain, altering translation efficiency. The structure of the entire 3'-UTR reveals that structurally distinct domains use a spine of continuously stacked bases and a strut-like linker to create a conduit for communication within the higher-order architecture. Thus, this 3'-UTR RNA illustrates how RNA can use programmed conformational changes to sense the translation status of an upstream open reading frame, then create a tuned functional response by communicating that information to other RNA elements.

RNA nanostructures and scaffolds for biotechnology applications

RNA plays important roles in the regulation of gene expressions and other cellular functions. It functions as both as an informational carrier and a nanomachine due to its complementary base-pairing ability and complexed three-dimensional structure. Several nanostructures have been designed and constructed by exploiting these natural RNA properties. In this review, we will introduce the design principles of RNA nanostructures and their biotechnology applications as molecular scaffolds. RNA-based molecular scaffolds can control the accumulation and interaction of target proteins at nanometer-scale to regulate the function of bacterial and mammalian cells. Combining useful property of RNA as a nano-material and a molecular scaffold may provide us powerful tools in biological research, bioengineering, and future medicine.

Bacterial riboswitches and RNA thermometers: Nature and contributions to pathogenesis

Bacterial pathogens are always challenged by fluctuations of chemical and physical parameters that pose serious threats to cellular integrity and metabolic status. Sudden deprivation of nutrients or key metabolites, changes in surrounding pH, and temperature shifts are the most important examples of such parameters. To elicit a proper response to such fluctuations, bacterial cells coordinate the expression of parameter-relevant genes. Although protein-mediated control of gene expression is well appreciated since many decades, RNA-based regulation has been discovered in early 2000s as a parallel level of regulation. Small regulatory RNAs have emerged as one of the most widespread and important gene regulatory systems in bacteria with rare representatives found in Archaea and Eukarya. Riboswitches and thermosensors are cis-encoded RNA regulatory elements that employ different mechanisms to regulate the expression of related genes controlling key metabolic pathways and genes of temperature relevant proteins including virulence factors. The extent of RNA contributions to gene regulation is not completely known even in well-studied models such E. coli and B. subtilis. In depth understanding of riboswitches is promising for opportunity to discover a narrow spectrum antibacterial drugs that target riboswitches of essential metabolic pathways.

Modeling Small Noncanonical RNA Motifs with the Rosetta FARFAR Server

Noncanonical RNA motifs help define the vast complexity of RNA structure and function, and in many cases, these loops and junctions are on the order of only ten nucleotides in size. Unfortunately, despite their small size, there is no reliable method to determine the ensemble of lowest energy structures of junctions and loops at atomic accuracy. This chapter outlines straightforward protocols using a webserver for Rosetta Fragment Assembly of RNA with Full Atom Refinement (FARFAR) ( http://rosie.rosettacommons.org/rna_denovo/submit ) to model the 3D structure of small noncanonical RNA motifs for use in visualizing motifs and for further refinement or filtering with experimental data such as NMR chemical shifts.

Single-Molecule Fluorescence Reveals Commonalities and Distinctions among Natural and in Vitro-Selected RNA Tertiary Motifs in a Multistep Folding Pathway

Decades of study of the RNA folding problem have revealed that diverse and complex structured RNAs are built from a common set of recurring structural motifs, leading to the perspective that a generalizable model of RNA folding may be developed from understanding of the folding properties of individual structural motifs. We used single-molecule fluorescence to dissect the kinetic and thermodynamic properties of a set of variants of a common tertiary structural motif, the tetraloop/tetraloop-receptor (TL/TLR). Our results revealed a multistep TL/TLR folding pathway in which preorganization of the ubiquitous AA-platform submotif precedes the formation of the docking transition state and tertiary A-minor hydrogen bond interactions form after the docking transition state. Differences in ion dependences between TL/TLR variants indicated the occurrence of sequence-dependent conformational rearrangements prior to and after the formation of the docking transition state. Nevertheless, varying the junction connecting the TL/TLR produced a common kinetic and ionic effect for all variants, suggesting that the global conformational search and compaction electrostatics are energetically independent from the formation of the tertiary motif contacts. We also found that in vitro-selected variants, despite their similar stability at high Mg²⁺ concentrations, are considerably less stable than natural variants under near-physiological ionic conditions, and the occurrence of the TL/TLR sequence variants in Nature correlates with their thermodynamic stability in isolation. Overall, our findings are consistent with modular but complex energetic properties of RNA structural motifs and will aid in the eventual quantitative description of RNA folding from its secondary and tertiary structural elements.

Occurrence and stability of lone pair-π stacking interactions between ribose and nucleobases in functional RNAs

The specific folding pattern and function of RNA molecules lies in various weak interactions, in addition to the strong base-base pairing and stacking. One of these relatively weak interactions, characterized by the stacking of the O4' atom of a ribose on top of the heterocycle ring of a nucleobase, has been known to occur but has largely been ignored in the description of RNA structures. We identified 2015 ribose-base stacking interactions in a high-resolution set of non-redundant RNA crystal structures. They are widespread in structured RNA molecules and are located in structural motifs other than regular stems. Over 50% of them involve an adenine, as we found ribose-adenine contacts to be recurring elements in A-minor motifs. Fewer than 50% of the interactions involve a ribose and a base of neighboring residues, while approximately 30% of them involve a ribose and a nucleobase at least four residues apart. Some of them establish inter-domain or inter-molecular contacts and often implicate functionally relevant nucleotides. In vacuo ribose-nucleobase stacking interaction energies were calculated by quantum mechanics methods. Finally, we found that lone pair-π stacking interactions also occur between ribose and aromatic amino acids in RNA-protein complexes.

Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs

Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.