Predicting RNA SHAPE scores with deep learning

Secondary structure prediction approaches rely typically on models of equilibrium free energies that are themselves based on in vitro physical chemistry. Recent transcriptome-wide experiments of in vivo RNA structure based on SHAPE-MaP experiments provide important information that may make it possible to extend current in vitro-based RNA folding models in order to improve the accuracy of computational RNA folding simulations with respect to the experimentally measured in vivo RNA secondary structure. Here we present a machine learning approach that utilizes RNA secondary structure prediction results and nucleotide sequence in order to predict in vivo SHAPE scores. We show that this approach has a higher Pearson correlation coefficient with experimental SHAPE scores than thermodynamic folding. This could be an important step towards augmenting experimental results with computational predictions and help with RNA secondary structure predictions that inherently take in-vivo folding properties into account.

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.

RiboSketch: versatile visualization of multi-stranded RNA and DNA secondary structure

Summary

Creating clear, visually pleasing 2D depictions of RNA and DNA strands and their interactions is important to facilitate and communicate insights related to nucleic acid structure. Here we present RiboSketch, a secondary structure image production application that enables the visualization of multistranded structures via layout algorithms, comprehensive editing capabilities, and a multitude of simulation modes. These interactive features allow RiboSketch to create publication quality diagrams for structures with a wide range of composition, size and complexity. The program may be run in any web browser without the need for installation, or as a standalone Java application.

Availability and implementation

https://rnastructure.cancer.gov/ribosketch.

A Suite of Therapeutically-Inspired Nucleic Acid Logic Systems for Conditional Generation of Single-Stranded and Double-Stranded Oligonucleotides

Several varieties of small nucleic acid constructs are able to modulate gene expression via one of a number of different pathways and mechanisms. These constructs can be synthesized, assembled and delivered to cells where they are able to impart regulatory functions, presenting a potential avenue for the development of nucleic acid-based therapeutics. However, distinguishing aberrant cells in need of therapeutic treatment and limiting the activity of deliverable nucleic acid constructs to these specific cells remains a challenge. Here, we designed and characterized a collection of nucleic acids systems able to generate and/or release sequence-specific oligonucleotide constructs in a conditional manner based on the presence or absence of specific RNA trigger molecules. The conditional function of these systems utilizes the implementation of AND and NOT Boolean logic elements, which could ultimately be used to restrict the release of functionally relevant nucleic acid constructs to specific cellular environments defined by the high or low expression of particular RNA biomarkers. Each system is generalizable and designed with future therapeutic development in mind. Every construct assembles through nuclease-resistant RNA/DNA hybrid duplex formation, removing the need for additional 2'-modifications, while none contain any sequence restrictions on what can define the diagnostic trigger sequence or the functional oligonucleotide output.

Functionally-interdependent shape-switching nanoparticles with controllable properties

We introduce a new concept that utilizes cognate nucleic acid nanoparticles which are fully complementary and functionally-interdependent to each other. In the described approach, the physical interaction between sets of designed nanoparticles initiates a rapid isothermal shape change which triggers the activation of multiple functionalities and biological pathways including transcription, energy transfer, functional aptamers and RNA interference. The individual nanoparticles are not active and have controllable kinetics of re-association and fine-tunable chemical and thermodynamic stabilities. Computational algorithms were developed to accurately predict melting temperatures of nanoparticles of various compositions and trace the process of their re-association in silico. Additionally, tunable immunostimulatory properties of described nanoparticles suggest that the particles that do not induce pro-inflammatory cytokines and high levels of interferons can be used as scaffolds to carry therapeutic oligonucleotides, while particles with strong interferon and mild pro-inflammatory cytokine induction may qualify as vaccine adjuvants. The presented concept provides a simple, cost-effective and straightforward model for the development of combinatorial regulation of biological processes in nucleic acid nanotechnology.

Triggerable RNA nanodevices

The targeted and conditional activation of pharmaceuticals is an increasingly important feature in modern personalized medicine. Nucleic acid nanoparticles show tremendous potential in this exploit due to their programmability and biocompatibility. Among the most powerful nucleic acid specific treatments is RNA interference-based therapeutics. RNA interference is a naturally occurring phenomenon in which specific genes are effectively silenced. Recently we have developed two different strategies based on customized multivalent nucleic acid nanoparticles with the ability to conditionally activate RNA interference in diseased cells as well as elicit detectable fluorescent responses.[1,2] These novel technologies can be further utilized for the simultaneous delivery and conditional intracellular activation of multiple therapeutic and biosensing functions to combat various diseases.

Preparation of a Conditional RNA Switch

RNA has gained great interest for use in biomedical and therapeutic applications. This is due in part to RNA's ability to perform multiple functions, including the regulation of endogenously expressed genes. However, the ability of RNA based drugs to distinguish target diseased cells from healthy tissue remains challenging. Here we present methods for the production of a recently developed conditional RNA switch that releases a Dicer substrate RNA in response to interaction with a specific RNA biomarker.

Computational Generation of RNA Nanorings

A variety of designed RNA ring structures (ranging from triangles to hexagonal rings) have been reported in the scientific literature. Designing self-assembling RNA ring structures from structural motifs is, however, a nontrivial problem as there are many combinations of motifs and linking helices. Moreover, most combinations of motifs and linker helices will not lead to ring closure. A solution to this problem was recently published using a "design-by-catalog" approach where motif combinations that lead to rings are precomputed and tabulated. Here we present a web-browser based workflow for creating RNA rings using Galaxy, a web-based platform that can be used for workflow management. An example of how these RNA rings are generated and processed to create a 3D model of the ring is discussed.

Cellular Delivery of RNA Nanoparticles

RNA nanostructures can be programmed to exhibit defined sizes, shapes and stoichiometries from naturally occurring or de novo designed RNA motifs. These constructs can be used as scaffolds to attach functional moieties, such as ligand binding motifs or gene expression regulators, for nanobiology applications. This review is focused on four areas of importance to RNA nanotechnology: the types of RNAs of particular interest for nanobiology, the assembly of RNA nanoconstructs, the challenges of cellular delivery of RNAs in vivo, and the delivery carriers that aid in the matter. The available strategies for the design of nucleic acid nanostructures, as well as for formulation of their carriers, make RNA nanotechnology an important tool in both basic research and applied biomedical science.

Ring Catalog: A resource for designing self-assembling RNA nanostructures

Designing self-assembling RNA ring structures based on known 3D structural elements connected via linker helices is a challenging task due to the immense number of motif combinations, many of which do not lead to ring-closure. We describe an in silico solution to this design problem by combinatorial assembly of RNA 3-way junctions, bulges, and kissing loops, and tabulating the cases that lead to ring formation. The solutions found are made available in the form of a web-accessible Ring Catalog. As an example of a potential use of this resource, we chose a predicted RNA square structure consisting of five RNA strands and demonstrate experimentally that the self-assembly of those five strands leads to the formation of a square-like complex. This is a demonstration of a novel "design by catalog" approach to RNA nano-structure generation. The URL https://rnajunction.ncifcrf.gov/ringdb can be used to access the resource.

The Use of Minimal RNA Toeholds to Trigger the Activation of Multiple Functionalities

Current work reports the use of single-stranded RNA toeholds of different lengths to promote the reassociation of various RNA-DNA hybrids, which results in activation of multiple split functionalities inside human cells. The process of reassociation is analyzed and followed with a novel computational multistrand secondary structure prediction algorithm and various experiments. All of our previously designed RNA/DNA nanoparticles employed single-stranded DNA toeholds to initiate reassociation. The use of RNA toeholds is advantageous because of the simpler design rules, the shorter toeholds, and the smaller size of the resulting nanoparticles (by up to 120 nucleotides per particle) compared to the same hybrid nanoparticles with single-stranded DNA toeholds. Moreover, the cotranscriptional assemblies result in higher yields for hybrid nanoparticles with ssRNA toeholds.

Multistrand Structure Prediction of Nucleic Acid Assemblies and Design of RNA Switches

RNA is an attractive material for the creation of molecular logic gates that release programmed functionalities only in the presence of specific molecular interaction partners. Here we present HyperFold, a multistrand RNA/DNA structure prediction approach for predicting nucleic acid complexes that can contain pseudoknots. We show that HyperFold also performs competitively compared to other published folding algorithms. We performed a large variety of RNA/DNA hybrid reassociation experiments for different concentrations, DNA toehold lengths, and G+C content and find that the observed tendencies for reassociation correspond well to computational predictions. Importantly, we apply this method to the design and experimental verification of a two-stranded RNA molecular switch that upon binding to a single-stranded RNA toehold disease-marker trigger mRNA changes its conformation releasing an shRNA-like Dicer substrate structure. To demonstrate the concept, connective tissue growth factor (CTGF) mRNA and enhanced green fluorescent protein (eGFP) mRNA were chosen as trigger and target sequences, respectively. In vitro experiments confirm the formation of an RNA switch and demonstrate that the functional unit is being released when the trigger RNA interacts with the switch toehold. The designed RNA switch is shown to be functional in MDA-MB-231 breast cancer cells. Several other switches were also designed and tested. We conclude that this approach has considerable potential because, in principle, it allows the release of an siRNA designed against a gene that differs from the gene that is utilized as a biomarker for a disease state.

Computational and experimental studies of reassociating RNA/DNA hybrids containing split functionalities

Recently, we developed a novel technique based on RNA/DNA hybrid reassociation that allows conditional activation of different split functionalities inside diseased cells and in vivo. We further expanded this idea to permit simultaneous activation of multiple different functions in a fully controllable fashion. In this chapter, we discuss some novel computational approaches and experimental techniques aimed at the characterization, design, and production of reassociating RNA/DNA hybrids containing split functionalities. We also briefly describe several experimental techniques that can be used to test these hybrids in vitro and in vivo.

In silico design and enzymatic synthesis of functional RNA nanoparticles

CONSPECTUS: The use of RNAs as scaffolds for biomedical applications has several advantages compared with other existing nanomaterials. These include (i) programmability, (ii) precise control over folding and self-assembly, (iii) natural functionalities as exemplified by ribozymes, riboswitches, RNAi, editing, splicing, and inherent translation and transcription control mechanisms, (iv) biocompatibility, (v) relatively low immune response, and (vi) relatively low cost and ease of production. We have tapped into several of these properties and functionalities to construct RNA-based functional nanoparticles (RNA NPs). In several cases, the structural core and the functional components of the NPs are inherent in the same construct. This permits control over the spatial disposition of the components, intracellular availability, and precise stoichiometry. To enable the generation of RNA NPs, a pipeline is being developed. On one end, it encompasses the rational design and various computational schemes that promote design of the RNA-based nanoconstructs, ultimately producing a set of sequences consisting of RNA or RNA-DNA hybrids, which can assemble into the designed construct. On the other end of the pipeline is an experimental component, which takes the produced sequences and uses them to initialize and characterize their proper assembly and then test the resulting RNA NPs for their function and delivery in cell culture and animal models. An important aspect of this pipeline is the feedback that constantly occurs between the computational and the experimental parts, which synergizes the refinement of both the algorithmic methodologies and the experimental protocols. The utility of this approach is depicted by the several examples described in this Account (nanocubes, nanorings, and RNA-DNA hybrids). Of particular interest, from the computational viewpoint, is that in most cases, first a three-dimensional representation of the assembly is produced, and only then are algorithms applied to generate the sequences that will assemble into the designated three-dimensional construct. This is opposite to the usual practice of predicting RNA structures from a given sequence, that is, the RNA folding problem. To be considered is the generation of sequences that upon assembly have the proper intra- or interstrand interactions (or both). Of particular interest from the experimental point of view is the determination and characterization of the proper thermodynamic, kinetic, functionality, and delivery protocols. Assembly of RNA NPs from individual single-stranded RNAs can be accomplished by one-pot techniques under the proper thermal and buffer conditions or, potentially more interestingly, by the use of various RNA polymerases that can promote the formation of RNA NPs cotransciptionally from specifically designed DNA templates. Also of importance is the delivery of the RNA NPs to the cells of interest in vitro or in vivo. Nonmodified RNAs rapidly degrade in blood serum and have difficulties crossing biological membranes due to their negative charge. These problems can be overcome by using, for example, polycationic lipid-based carriers. Our work involves the use of bolaamphiphiles, which are amphipathic compounds with positively charged hydrophilic head groups at each end connected by a hydrophobic chain. We have correlated results from molecular dynamics computations with various experiments to understand the characteristics of such delivery agents.

Computational and experimental characterization of RNA cubic nanoscaffolds

The fast-developing field of RNA nanotechnology requires the adoption and development of novel and faster computational approaches to modeling and characterization of RNA-based nano-objects. We report the first application of Elastic Network Modeling (ENM), a structure-based dynamics model, to RNA nanotechnology. With the use of an Anisotropic Network Model (ANM), a type of ENM, we characterize the dynamic behavior of non-compact, multi-stranded RNA-based nanocubes that can be used as nano-scale scaffolds carrying different functionalities. Modeling the nanocubes with our tool NanoTiler and exploring the dynamic characteristics of the models with ANM suggested relatively minor but important structural modifications that enhanced the assembly properties and thermodynamic stabilities. In silico and in vitro, we compared nanocubes having different numbers of base pairs per side, showing with both methods that the 10 bp-long helix design leads to more efficient assembly, as predicted computationally. We also explored the impact of different numbers of single-stranded nucleotide stretches at each of the cube corners and showed that cube flexibility simulations help explain the differences in the experimental assembly yields, as well as the measured nanomolecule sizes and melting temperatures. This original work paves the way for detailed computational analysis of the dynamic behavior of artificially designed multi-stranded RNA nanoparticles.

Co-transcriptional production of RNA-DNA hybrids for simultaneous release of multiple split functionalities

Control over the simultaneous delivery of different functionalities and their synchronized intracellular activation can greatly benefit the fields of RNA and DNA biomedical nanotechnologies and allow for the production of nanoparticles and various switching devices with controllable functions. We present a system of multiple split functionalities embedded in the cognate pairs of RNA-DNA hybrids which are programmed to recognize each other, re-associate and form a DNA duplex while also releasing the split RNA fragments which upon association regain their original functions. Simultaneous activation of three different functionalities (RNAi, Förster resonance energy transfer and RNA aptamer) confirmed by multiple in vitro and cell culture experiments prove the concept. To automate the design process, a novel computational tool that differentiates between the thermodynamic stabilities of RNA-RNA, RNA-DNA and DNA-DNA duplexes was developed. Moreover, here we demonstrate that besides being easily produced by annealing synthetic RNAs and DNAs, the individual hybrids carrying longer RNAs can be produced by RNA polymerase II-dependent transcription of single-stranded DNA templates.

Genomic analyses reveal broad impact of miR-137 on genes associated with malignant transformation and neuronal differentiation in glioblastoma cells

miR-137 plays critical roles in the nervous system and tumor development; an increase in its expression is required for neuronal differentiation while its reduction is implicated in gliomagenesis. To evaluate the potential of miR-137 in glioblastoma therapy, we conducted genome-wide target mapping in glioblastoma cells by measuring the level of association between PABP and mRNAs in cells transfected with miR-137 mimics vs. controls via RIPSeq. Impact on mRNA levels was also measured by RNASeq. By combining the results of both experimental approaches, 1468 genes were found to be negatively impacted by miR-137--among them, 595 (40%) contain miR-137 predicted sites. The most relevant targets include oncogenic proteins and key players in neurogenesis like c-KIT, YBX1, AKT2, CDC42, CDK6 and TGFβ2. Interestingly, we observed that several identified miR-137 targets are also predicted to be regulated by miR-124, miR-128 and miR-7, which are equally implicated in neuronal differentiation and gliomagenesis. We suggest that the concomitant increase of these four miRNAs in neuronal stem cells or their repression in tumor cells could produce a robust regulatory effect with major consequences to neuronal differentiation and tumorigenesis.

The favorable IFNL3 genotype escapes mRNA decay mediated by AU-rich elements and hepatitis C virus-induced microRNAs

IFNL3, which encodes interferon-λ3 (IFN-λ3), has received considerable attention in the hepatitis C virus (HCV) field, as many independent genome-wide association studies have identified a strong association between polymorphisms near IFNL3 and clearance of HCV. However, the mechanism underlying this association has remained elusive. In this study, we report the identification of a functional polymorphism (rs4803217) in the 3' untranslated region (UTR) of IFNL3 mRNA that dictated transcript stability. We found that this polymorphism influenced AU-rich element (ARE)-mediated decay (AMD) of IFNL3 mRNA, as well as the binding of HCV-induced microRNAs during infection. Together these pathways mediated robust repression of the unfavorable IFNL3 polymorphism. Our data reveal a previously unknown mechanism by which HCV attenuates the antiviral response and indicate new potential therapeutic targets for HCV treatment.

Computational detection of abundant long-range nucleotide covariation in Drosophila genomes

Functionally important nucleotide base-pairing often manifests itself in sequence alignments in the form of compensatory base changes (covariation). We developed a novel index-based computational method (CovaRNA) to detect long-range covariation on a genomic scale, as well as another computational method (CovStat) for determining the statistical significance of observed covariation patterns in alignment pairs. Here we present an all-versus-all search for nucleotide covariation in Drosophila genomic alignments. The search is genome wide, with the restriction that only alignments that correspond to euchromatic regions, which consist of at least 10 Drosophila species, are being considered (59% of the euchromatic genome of Drosophila melanogaster). We find that long-range covariations are especially prevalent between exons of mRNAs as well as noncoding RNAs; the majority of the observed covariations appear as not reverse complementary, but as synchronized mutations, which could be due to interactions with common interaction partners or due to the involvement of genomic elements that are antisense of annotated transcripts. The involved genes are enriched for functions related to regionalization as well as neural and developmental processes. These results are computational evidence that RNA-RNA long-range interactions are a widespread phenomenon that is of fundamental importance to a variety of cellular processes.

MicroRNA-29 Stabilizes IFN-γ mRNA by inhibiting GW182 (174.5)

Tight regulation of interferon-gamma (IFN-γ) expression is critical for an optimal immune response. We have extensively studied the mechanisms responsible for the post-transcriptional regulation of IFN-γ expression. AU-rich element (ARE)-mediated decay (AMD) via the tristetraprolin (TTP) complex is responsible for robust degradation of the IFN-γ mRNA. We found that microRNA-29 (miR-29) targets the IFN-γ 3’UTR and, unlike the conventional inhibitory miRNAs, stabilizes the mRNA. Resolution of the secondary structure showed that the ARE and miR-29 binding site are in close proximity and a series of experiments manipulating the RNA structure revealed that this proximity enables miR-29 to antagonize TTP degradation. Interestingly, miR-29 is unable to degrade the mRNA even in the absence of TTP. Recently we have found that GW182, a major degradation protein in the miRISC, is unable to be recruited to the mRNA as a result of the location of the miR-29 binding site in the secondary structure. The ability of miR-29 to stabilize the IFN-γ mRNA demonstrates a novel molecular mechanism of miRNA regulation.

Multistrand RNA secondary structure prediction and nanostructure design including pseudoknots

We are presenting NanoFolder, a method for the prediction of the base pairing of potentially pseudoknotted multistrand RNA nanostructures. We show that the method outperforms several other structure prediction methods when applied to RNA complexes with non-nested base pairs. We extended this secondary structure prediction capability to allow RNA sequence design. Using native PAGE, we experimentally confirm that four in silico designed RNA strands corresponding to a triangular RNA structure form the expected stable complex.

Design and self-assembly of siRNA-functionalized RNA nanoparticles for use in automated nanomedicine

Individual genes can be targeted with siRNAs. The use of nucleic acid nanoparticles (NPs) is a convenient method for delivering combinations of specific siRNAs in an organized and programmable manner. We present three assembly protocols to produce two different types of RNA self-assembling functional NPs using processes that are fully automatable. These NPs are engineered based on two complementary nanoscaffold designs (nanoring and nanocube), which serve as carriers of multiple siRNAs. The NPs are functionalized by the extension of up to six scaffold strands with siRNA duplexes. The assembly protocols yield functionalized RNA NPs, and we show that they interact in vitro with human recombinant Dicer to produce siRNAs. Our design strategies allow for fast, economical and easily controlled production of endotoxin-free therapeutic RNA NPs that are suitable for preclinical development.

Correlating SHAPE signatures with three-dimensional RNA structures

Selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) is a facile technique for quantitative analysis of RNA secondary structure. In general, low SHAPE signal values indicate Watson-Crick base-pairing, and high values indicate positions that are single-stranded within the RNA structure. However, the relationship of SHAPE signals to structural properties such as non-Watson-Crick base-pairing or stacking has thus far not been thoroughly investigated. Here, we present results of SHAPE experiments performed on several RNAs with published three-dimensional structures. This strategy allows us to analyze the results in terms of correlations between chemical reactivities and structural properties of the respective nucleotide, such as different types of base-pairing, stacking, and phosphate-backbone interactions. We find that the RNA SHAPE signal is strongly correlated with cis-Watson-Crick/Watson-Crick base-pairing and is to a remarkable degree not dependent on other structural properties with the exception of stacking. We subsequently generated probabilistic models that estimate the likelihood that a residue with a given SHAPE score participates in base-pairing. We show that several models that take SHAPE scores of adjacent residues into account perform better in predicting base-pairing compared with individual SHAPE scores. This underscores the context sensitivity of SHAPE and provides a framework for an improved interpretation of the response of RNA to chemical modification.

Use of RNA structure flexibility data in nanostructure modeling

In the emerging field of RNA-based nanotechnology there is a need for automation of the structure design process. Our goal is to develop computer methods for aiding in this process. Towards that end, we created the RNA junction database, which is a repository of RNA junctions, i.e. internal, multi-branch and kissing loops with emanating stem stubs, extracted from the larger RNA structures stored in the PDB database. These junctions can be used as building blocks for nanostructures. Two programs developed in our laboratory, NanoTiler and RNA2D3D, can combine such building blocks with idealized fragments of A-form helices to produce desired 3D nanostructures. Initially, the building blocks are treated as rigid objects and the resulting geometry is tested against the design objectives. Experimental data, however, shows that RNA accommodates its shape to the constraints of larger structural contexts. Therefore we are adding analysis of the flexibility of our building blocks to the full design process. Here we present an example of RNA-based nanostructure design, putting emphasis on the need to characterize the structural flexibility of the building blocks to induce ring closure in the automated exploration. We focus on the use of kissing loops (KL) in nanostructure design, since they have been shown to play an important role in RNA self-assembly. By using an experimentally proven system, the RNA tectosquare, we show that considering the flexibility of the KLs as well as distortions of helical regions may be necessary to achieve a realistic design.

MicroRNA-29 stabilizes interferon-gamma mRNA by antagonizing AU-rich element-mediated decay (57.3)

Tight regulation of interferon-gamma (IFN-g) expression is critical for an optimal immune response. IFN-g mRNA levels are attenuated by AU-rich element (ARE)-mediated decay (AMD) via the tristetraprolin (TTP) complex. Here we show that miR-29 targets the 3'untranslated region of IFN-g mRNA and unlike the conventional inhibitory function of miRNAs, increases IFN-g protein expression by stabilizing the mRNA. Through analysis of RNA structure derived by chemoenzymatic probing, we demonstrate that the AMD function is blocked by a miR-29 induced RNA conformational switch that makes the TTP binding site inaccessible. This effectively results in competition between the miRNA-induced silencing complex and TTP for post-transcriptional control of IFN-g gene expression. Our proposed role of miR-29 in stabilizing IFN-g provides a novel molecular mechanism of miRNA regulation and presents new targets for the manipulation of the immune system in the treatment of human diseases.

In vitro assembly of cubic RNA-based scaffolds designed in silico

The organization of biological materials into versatile three-dimensional assemblies could be used to build multifunctional therapeutic scaffolds for use in nanomedicine. Here, we report a strategy to design three-dimensional nanoscale scaffolds that can be self-assembled from RNA with precise control over their shape, size and composition. These cubic nanoscaffolds are only approximately 13 nm in diameter and are composed of short oligonucleotides, making them amenable to chemical synthesis, point modifications and further functionalization. Nanocube assembly is verified by gel assays, dynamic light scattering and cryogenic electron microscopy. Formation of functional RNA nanocubes is also demonstrated by incorporation of a light-up fluorescent RNA aptamer that is optimally active only upon full RNA assembly. Moreover, we show that the RNA nanoscaffolds can self-assemble in isothermal conditions (37 degrees C) during in vitro transcription, which opens a route towards the construction of sensors, programmable packaging and cargo delivery systems for biomedical applications.

CyloFold: secondary structure prediction including pseudoknots

Computational RNA secondary structure prediction approaches differ by the way RNA pseudoknot interactions are handled. For reasons of computational efficiency, most approaches only allow a limited class of pseudoknot interactions or are not considering them at all. Here we present a computational method for RNA secondary structure prediction that is not restricted in terms of pseudoknot complexity. The approach is based on simulating a folding process in a coarse-grained manner by choosing helices based on established energy rules. The steric feasibility of the chosen set of helices is checked during the folding process using a highly coarse-grained 3D model of the RNA structures. Using two data sets of 26 and 241 RNA sequences we find that this approach is competitive compared to the existing RNA secondary structure prediction programs pknotsRG, HotKnots and UnaFold. The key advantages of the new method are that there is no algorithmic restriction in terms of pseudoknot complexity and a test is made for steric feasibility.

AVAILABILITY

The program is available as web server at the site: http://cylofold.abcc.ncifcrf.gov.

Role of 3'UTRs in the translation of mRNAs regulated by oncogenic eIF4E--a computational inference

Eukaryotic cap-dependent mRNA translation is mediated by the initiation factor eIF4E, which binds mRNAs and stimulates efficient translation initiation. eIF4E is often overexpressed in human cancers. To elucidate the molecular signature of eIF4E target mRNAs, we analyzed sequence and structural properties of two independently derived polyribosome recruited mRNA datasets. These datasets originate from studies of mRNAs that are actively being translated in response to cells over-expressing eIF4E or cells with an activated oncogenic AKT: eIF4E signaling pathway, respectively. Comparison of eIF4E target mRNAs to mRNAs insensitive to eIF4E-regulation has revealed surprising features in mRNA secondary structure, length and microRNA-binding properties. Fold-changes (the relative change in recruitment of an mRNA to actively translating polyribosomal complexes in response to eIF4E overexpression or AKT upregulation) are positively correlated with mRNA G+C content and negatively correlated with total and 3′UTR length of the mRNAs. A machine learning approach for predicting the fold change was created. Interesting tendencies of secondary structure stability are found near the start codon and at the beginning of the 3′UTR region. Highly upregulated mRNAs show negative selection (site avoidance) for binding sites of several microRNAs. These results are consistent with the emerging model of regulation of mRNA translation through a dynamic balance between translation initiation at the 5′UTR and microRNA binding at the 3′UTR.

Computational strategies for the automated design of RNA nanoscale structures from building blocks using NanoTiler

One approach to designing RNA nanoscale structures is to use known RNA structural motifs such as junctions, kissing loops or bulges and to construct a molecular model by connecting these building blocks with helical struts. We previously developed an algorithm for detecting internal loops, junctions and kissing loops in RNA structures. Here we present algorithms for automating or assisting many of the steps that are involved in creating RNA structures from building blocks: (1) assembling building blocks into nanostructures using either a combinatorial search or constraint satisfaction; (2) optimizing RNA 3D ring structures to improve ring closure; (3) sequence optimisation; (4) creating a unique non-degenerate RNA topology descriptor. This effectively creates a computational pipeline for generating molecular models of RNA nanostructures and more specifically RNA ring structures with optimized sequences from RNA building blocks. We show several examples of how the algorithms can be utilized to generate RNA tecto-shapes.

Protocols for the in silico design of RNA nanostructures

Recent developments in the field of nanobiology have significantly expanded the possibilities for new modalities in the treatment of many diseases, including cancer. Ribonucleic acid (RNA) represents a relatively new molecular material for the development of these biologically oriented nanodevices. In addition, RNA nanobiology presents a relatively new approach for the development of RNA-based nanoparticles that can be used as crystallization substrates and scaffolds for RNA-based nanoarrays. Presented in this chapter are some methodological shaped-based protocols for the design of such RNA nanostructures. Included are descriptions and background materials describing protocols that use a database of three-dimensional RNA structure motifs; designed RNA secondary structure motifs; and a combination of the two approaches. An example is also given illustrating one of the protocols.

RNAJunction: a database of RNA junctions and kissing loops for three-dimensional structural analysis and nanodesign

We developed a database called RNAJunction that contains structure and sequence information for RNA structural elements such as helical junctions, internal loops, bulges and loop-loop interactions. Our database provides a user-friendly way of searching structural elements by PDB code, structural classification, sequence, keyword or inter-helix angles. In addition, the structural data was subjected to energy minimization. This database is useful for analyzing RNA structures as well as for designing novel RNA structures on a nanoscale. The database can be accessed at: http://rnajunction.abcc.ncifcrf.gov/

Bridging the gap in RNA structure prediction

The field of RNA structure prediction has experienced significant advances in the past several years, thanks to the availability of new experimental data and improved computational methodologies. These methods determine RNA secondary structures and pseudoknots from sequence alignments, thermodynamics-based dynamic programming algorithms, genetic algorithms and combined approaches. Computational RNA three-dimensional modeling uses this information in conjunction with manual manipulation, constraint satisfaction methods, molecular mechanics and molecular dynamics. The ultimate goal of automatically producing RNA three-dimensional models from given secondary and tertiary structure data, however, is still not fully realized. Recent developments in the computational prediction of RNA structure have helped bridge the gap between RNA secondary structure prediction, including pseudoknots, and three-dimensional modeling of RNA.

Align: a C++ class library and web server for rapid sequence alignment prototyping

Sequence alignment remains a fundamental tool in most tasks related to the prediction of protein sequence and structure. A C++ class library was developed to facilitate the rapid implementation of a variety of state-of-the-art pairwise sequence alignment techniques. These range from simple sequence to sequence to the advanced profile to profile alignments with optional secondary structure information. Suboptimal alignments, frequently used to estimate regions of confidence, can also be generated. The object oriented design facilitates rapid implementation, testing and extension of existing functionality. A simple web interface, which can also be useful in bioinformatics education, is also provided. Source code, online documentation and a prototypical web interface are freely accessible to academic users from the URL: http://protein.cribi.unipd.it/align/. A sample case study in the modelling of human Cytochrome P450 is discussed.

CorreLogo: an online server for 3D sequence logos of RNA and DNA alignments

We present an online server that generates a 3D representation of properties of user-submitted RNA or DNA alignments. The visualized properties are information of single alignment columns, mutual information of two alignment positions as well as the position-specific fraction of gaps. The nucleotide composition of both single columns and column pairs is visualized with the help of color-coded 3D bars labeled with letters. The server generates both VRML and JVX output that can be viewed with a VRML viewer or the JavaView applet, respectively. We show that combining these different features of an alignment into one 3D representation is helpful in identifying correlations between bases and potential RNA and DNA base pairs. Significant known correlations between the tRNA 3′ anticodon cardinal nucleotide and the extended anticodon were observed, as were correlations within the amino acid acceptor stem and between the cardinal nucleotide and the acceptor stem. The online server can be accessed using the URL .

RNA secondary structure prediction from sequence alignments using a network of k-nearest neighbor classifiers

We present a machine learning method (a hierarchical network of k-nearest neighbor classifiers) that uses an RNA sequence alignment in order to predict a consensus RNA secondary structure. The input to the network is the mutual information, the fraction of complementary nucleotides, and a novel consensus RNAfold secondary structure prediction of a pair of alignment columns and its nearest neighbors. Given this input, the network computes a prediction as to whether a particular pair of alignment columns corresponds to a base pair. By using a comprehensive test set of 49 RFAM alignments, the program KNetFold achieves an average Matthews correlation coefficient of 0.81. This is a significant improvement compared with the secondary structure prediction methods PFOLD and RNAalifold. By using the example of archaeal RNase P, we show that the program can also predict pseudoknot interactions.

Structural polymorphism of the HIV-1 leader region explored by computational methods

Experimental studies revealed that the elements of the human immunodeficiency virus type 1 (HIV-1) 5′-untranslated leader region (5′-UTR) can fold in vitro into two alternative conformations, branched (BMH) and ‘linearized’ (LDI) and switch between them to achieve different functionality. In this study we computationally explored in detail, with our massively parallel genetic algorithm (MPGAfold), the propensity of 13 HIV-1 5′-UTRs to fold into the BMH and the LDI conformation types. Besides the BMH conformations these results predict the existence of two functionally equivalent types of LDI conformations. One is similar to what has been shown in vitro to exist in HIV-1 LAI, the other is a novel conformation exemplified by HIV-1 MAL long-distance interactions. These novel MPGAfold results are further corroborated by a consensus probability matrix algorithm applied to a set of 155 HIV-1 sequences. We also have determined in detail the impact of various strain mutations, domain sizes and folds of elongating sequences simulating folding during transcription on HIV-1 RNA secondary structure folding dynamics.

A scoring function for docking ligands to low-resolution protein structures

We present a docking method that uses a scoring function for protein-ligand docking that is designed to maximize the docking success rate for low-resolution protein structures. We find that the resulting scoring function parameters are very different depending on whether they were optimized for high- or low-resolution protein structures. We show that this docking method can be successfully applied to predict the ligand-binding site of low-resolution structures. For a set of 25 protein-ligand complexes, in 76% of the cases, more than 50% of ligand-contacting residues are correctly predicted (using receptor crystal structures where the binding site is unspecified). Using decoys of the receptor structures having a 4 A RMSD from the native structure, for the same set of complexes, in 72% of the cases, we obtain at least one correctly predicted ligand-contacting residue. Furthermore, using an 81-protein-ligand set described by Jain, in 76 (93.8%) cases, the algorithm correctly predicts more than 50% of the ligand-contacting residues when native protein structures are used. Using 3 A RMSD from native decoys, in all but two cases (97.5%), the algorithm predicts at least one ligand-binding residue correctly. Finally, compared to the previously published Dolores method, for 298 protein-ligand pairs, the number of cases in which at least half of the specific contacts are correctly predicted is more than four times greater.

The SSEA server for protein secondary structure alignment

SUMMARY

We present a web server that computes alignments of protein secondary structures. The server supports both performing pairwise alignments and searching a secondary structure against a library of domain folds. It can calculate global and local secondary structure element alignments. A combination of local and global alignment steps can be used to search for domains inside the query sequence or help in the discrimination of novel folds. Both the SCOP and PDB fold libraries, clustered at 95 and 40% sequence identity, are available for alignment.

AVAILABILITY

The web server interface is freely accessible to academic users at http://protein.cribi.unipd.it/ssea/. The executable version and benchmarking data are available from the same web page.

MANIFOLD: protein fold recognition based on secondary structure, sequence similarity and enzyme classification

We present a protein fold recognition method, MANIFOLD, which uses the similarity between target and template proteins in predicted secondary structure, sequence and enzyme code to predict the fold of the target protein. We developed a non-linear ranking scheme in order to combine the scores of the three different similarity measures used. For a difficult test set of proteins with very little sequence similarity, the program predicts the fold class correctly in 34% of cases. This is an over twofold increase in accuracy compared with sequence-based methods such as PSI-BLAST or GenTHREADER, which score 13-14% correct first hits for the same test set. The functional similarity term increases the prediction accuracy by up to 3% compared with using the combination of secondary structure similarity and PSI-BLAST alone. We argue that using functional and secondary structure information can increase the fold recognition beyond sequence similarity.

A divide and conquer approach to fast loop modeling

We describe a fast ab initio method for modeling local segments in protein structures. The algorithm is based on a divide and conquer approach and uses a database of precalculated look-up tables, which represent a large set of possible conformations for loop segments of variable length. The target loop is recursively decomposed until the resulting conformations are small enough to be compiled analytically. The algorithm, which is not restricted to any specific loop length, generates a ranked set of loop conformations in 20-180 s on a desktop PC. The prediction quality is evaluated in terms of global RMSD. Depending on loop length the top prediction varies between 1.06 A RMSD for three-residue loops and 3.72 A RMSD for eight-residue loops. Due to its speed the method may also be useful to generate alternative starting conformations for complex simulations.

Visualization of fast energy flow and solvent caging in unimolecular dynamics

Energy flow in solution between physically or chemically evolving solute molecules and the surrounding solvent significantly affects the nature of chemical dynamics in liquids. It determines the extent to which the statistical theory of reaction rates is valid; the transfer of energy between solute and solvent influences the ease with which the transition state evolves into the products--the process central to transition-state theory. But analysing the energy flow in liquid-phase dynamics is difficult because these systems are so complex, and the degrees of freedom are consequently so numerous. Here we present a way to address this challenge. We introduce an approach for visualizing the energy flow directly, and apply it to the isomerization of cyclohexane (between boat and chair conformations) in liquid carbon disulphide, a process for which detailed information about the molecular motions is available from molecular dynamics simulations. Our method reveals in pictorial form the formation and relaxation of a solvent cage, and shows that the relaxation has a strong effect on energy flow to and from the transition state on sub-picosecond timescales. We anticipate that this visualization approach will be generally useful for elucidating dynamical molecular processes in solution.