Predicting thermodynamic properties of RNA

A nucleotide-level coarse-grained model of RNA

We present a new, nucleotide-level model for RNA, oxRNA, based on the coarse-graining methodology recently developed for the oxDNA model of DNA. The model is designed to reproduce structural, mechanical, and thermodynamic properties of RNA, and the coarse-graining level aims to retain the relevant physics for RNA hybridization and the structure of single- and double-stranded RNA. In order to explore its strengths and weaknesses, we test the model in a range of nanotechnological and biological settings. Applications explored include the folding thermodynamics of a pseudoknot, the formation of a kissing loop complex, the structure of a hexagonal RNA nanoring, and the unzipping of a hairpin motif. We argue that the model can be used for efficient simulations of the structure of systems with thousands of base pairs, and for the assembly of systems of up to hundreds of base pairs. The source code implementing the model is released for public use.

Semisynthetic tRNA complement mediates in vitro protein synthesis

Genetic code expansion is a key objective of synthetic biology and protein engineering. Most efforts in this direction are focused on reassigning termination or decoding quadruplet codons. While the redundancy of genetic code provides a large number of potentially reassignable codons, their utility is diminished by the inevitable interaction with cognate aminoacyl-tRNAs. To address this problem, we sought to establish an in vitro protein synthesis system with a simplified synthetic tRNA complement, thereby orthogonalizing some of the sense codons. This quantitative in vitro peptide synthesis assay allowed us to analyze the ability of synthetic tRNAs to decode all of 61 sense codons. We observed that, with the exception of isoacceptors for Asn, Glu, and Ile, the majority of 48 synthetic Escherichia coli tRNAs could support protein translation in the cell-free system. We purified to homogeneity functional Asn, Glu, and Ile tRNAs from the native E. coli tRNA mixture, and by combining them with synthetic tRNAs, we formulated a semisynthetic tRNA complement for all 20 amino acids. We further demonstrated that this tRNA complement could restore the protein translation activity of tRNA-depleted E. coli lysate to a level comparable to that of total native tRNA. To confirm that the developed system could efficiently synthesize long polypeptides, we expressed three different sequences coding for superfolder GFP. This novel semisynthetic translation system is a powerful tool for tRNA engineering and potentially enables the reassignment of at least 9 sense codons coding for Ser, Arg, Leu, Pro, Thr, and Gly.

Design, synthesis, and application of Spinach molecular beacons triggered by strand displacement

We describe design parameters for the synthesis and analytical application of a label-free RNA molecular beacon, termed Spinach.ST. The RNA aptamer Spinach fluoresces upon binding the small-molecule fluorophore DFHBI ((Z)-4-(3,5-difluoro-4-hydroxybenzylidene)-1,2-dimethyl-1H-imidazol-5(4H)-one). Spinach has been reengineered by extending its 5'- and 3'-ends to create Spinach.ST, which is predicted to fold into an inactive conformation that fails to bind DHFBI. Hybridization of a trigger oligonucleotide to a designed toehold on Spinach.ST initiates toehold-mediated strand displacement and restores the DFHBI-binding, fluorescence-enhancing conformation of Spinach. The versatile Spinach.ST sensor can detect DNA or RNA trigger sequences and can readily distinguish single-nucleotide mismatches in the trigger toehold. Primer design techniques are described that augment amplicons produced by enzymatic amplification with Spinach.ST triggers. Interaction between these triggers and Spinach.ST molecular beacons leads to the real-time, sequence-specific quantitation of these amplicons. The use of Spinach.ST with isothermal amplification reactions such as nucleic acid sequence-based amplification (NASBA) may enable point-of-care applications. The same design principles could also be used to adapt Spinach reporters to the assay of nonnucleic acid analytes in trans.

Computational tools and algorithms for designing customized synthetic genes

Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.

A remarkably stable kissing-loop interaction defines substrate recognition by the Neurospora Varkud Satellite ribozyme

Kissing loops are tertiary structure elements that often play key roles in functional RNAs. In the Neurospora VS ribozyme, a kissing-loop interaction between the stem-loop I (SLI) substrate and stem-loop V (SLV) of the catalytic domain is known to play an important role in substrate recognition. In addition, this I/V kissing-loop interaction is associated with a helix shift in SLI that activates the substrate for catalysis. To better understand the role of this kissing-loop interaction in substrate recognition and activation by the VS ribozyme, we performed a thermodynamic characterization by isothermal titration calorimetry using isolated SLI and SLV stem-loops. We demonstrate that preshifted SLI variants have higher affinity for SLV than shiftable SLI variants, with an energetic cost of 1.8-3 kcal/mol for the helix shift in SLI. The affinity of the preshifted SLI for SLV is remarkably high, the interaction being more stable by 7-8 kcal/mol than predicted for a comparable duplex containing three Watson-Crick base pairs. The structural basis of this remarkable stability is discussed in light of previous NMR studies. Comparative thermodynamic studies reveal that kissing-loop complexes containing 6-7 Watson-Crick base pairs are as stable as predicted from comparable RNA duplexes; however, those with 2-3 Watson-Crick base pairs are more stable than predicted. Interestingly, the stability of SLI/ribozyme complexes is similar to that of SLI/SLV complexes. Thus, the I/V kissing loop interaction represents the predominant energetic contribution to substrate recognition by the trans-cleaving VS ribozyme.

A Spinach molecular beacon triggered by strand displacement

We have re-engineered the fluorescent RNA aptamer Spinach to be activated in a sequence-dependent manner. The original Spinach aptamer was extended at its 5'- and 3'-ends to create Spinach.ST, which is predicted to fold into an inactive conformation and thus prevent association with the small molecule fluorophore DFHBI. Hybridization of a specific trigger oligonucleotide to a designed toehold leads to toehold-initiated strand displacement and refolds Spinach into the active, fluorophore-binding conformation. Spinach.ST not only specifically detects its target oligonucleotide but can discriminate readily against single-nucleotide mismatches. RNA amplicons produced during nucleic acid sequence-based amplification (NASBA) of DNA or RNA targets could be specifically detected and reported in real-time by conformational activation of Spinach.ST generated by in vitro transcription. In order to adapt any target sequence to detection by a Spinach reporter we used a primer design technique that brings together otherwise distal toehold sequences via hairpin formation. The same techniques could potentially be used to adapt common Spinach reporters to non-nucleic acid analytes, rather than by making fusions between aptamers and Spinach.

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

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

Highly conserved RNA pseudoknots at the Gag-Pol junction of HIV-1 suggest a novel mechanism of -1 ribosomal frameshifting

-1 programmed ribosomal frameshifting (PRF) is utilized by many viruses to synthesize their enzymatic (Pol) and structural (Gag) proteins at a defined ratio. For efficient -1 PRF, two cis-acting elements are required: a heptanucleotide frameshift site and a downstream stimulator such as a pseudoknot. We have analyzed the gag-pol junction sequences from 4254 HIV-1 strains. Approximately ninety-five percent of the sequences can form four pseudoknots PK1-PK4 (∼ 97% contain PK1, PK3, and PK4), covering ∼ 72 nt including the frameshift site. Some pseudoknots are mutually excluded due to sequence overlap. PK1 and PK3 arrange tandemly. Their stems form a quasi-continuous helix of ∼ 22 bp. We propose a novel mechanism for possible roles of these pseudoknots. Multiple alternative structures may exist at the gag-pol junction. In most strains, the PK1-PK3 tandem pseudoknots may dominate the structurally heterogeneous pool of RNA due to their greater overall stability. The tandem pseudoknots may function as a breaking system to slow down the ribosome. The ribosome unwinds PK1 and stem 1 of PK3 before it can reach the frameshift site. Then, PK4 can form rapidly because the intact stem 2 of PK3 makes up a large part of the stem 1 of PK4. The newly formed PK4 jams the entrance of the mRNA tunnel. The process then proceeds as in a typical case of -1 PRF. This mechanism incorporates several exquisite new features while still being consistent with the current paradigm of pseudoknot-dependent -1 PRF.

A genome-wide analysis of RNA pseudoknots that stimulate efficient -1 ribosomal frameshifting or readthrough in animal viruses

Programmed −1 ribosomal frameshifting (PRF) and stop codon readthrough are two translational recoding mechanisms utilized by some RNA viruses to express their structural and enzymatic proteins at a defined ratio. Efficient recoding usually requires an RNA pseudoknot located several nucleotides downstream from the recoding site. To assess the strategic importance of the recoding pseudoknots, we have carried out a large scale genome-wide analysis in which we used an in-house developed program to detect all possible H-type pseudoknots within the genomic mRNAs of 81 animal viruses. Pseudoknots are detected downstream from ~85% of the recoding sites, including many previously unknown pseudoknots. ~78% of the recoding pseudoknots are the most stable pseudoknot within the viral genomes. However, they are not as strong as some designed pseudoknots that exhibit roadblocking effect on the translating ribosome. Strong roadblocking pseudoknots are not detected within the viral genomes. These results indicate that the decoding pseudoknots have evolved to possess optimal stability for efficient recoding. We also found that the sequence at the gag-pol frameshift junction of HIV1 harbors potential elaborated pseudoknots encompassing the frameshift site. A novel mechanism is proposed for possible involvement of the elaborated pseudoknots in the HIV1 PRF event.

CpG usage in RNA viruses: data and hypotheses

CpG repression in RNA viruses has been known for decades, but a reasonable explanation has not yet been proposed to explain this phenomenon. In this study, we calculated the CpG odds ratio of all RNA viruses that have available genome sequences and analyzed the correlation with their genome polarity, base composition, synonymous codon usage, phylogenetic relationship, and host. The results indicated that the viral base composition, synonymous codon usage and host selection were the dominant factors that determined the CpG bias in RNA viruses. CpG usage variation between the different viral groups was caused by different combinations of these pressures, which also differed from each other in strength. The consistent under-representation of CpG usage in −ssRNA viruses is determined predominantly by base composition, which may be a consequence of the U/A preferred mutation bias of −ssRNA viruses, whereas the CpG usage of +ssRNA viruses is affected greatly by their hosts. As a result, most +ssRNA viruses mimic their hosts' CpG usage. Unbiased CpG usage in dsRNA viruses is most likely a result of their dsRNA genome, which allows the viruses to escape from the host-driven CpG elimination pressure. CpG was under-represented in all reverse-transcribing viruses (RT viruses), suggesting that DNA methylation is an important factor affecting the CpG usage of retroviruses. However, vertebrate-infecting RT viruses may also suffer host' CpG elimination pressure that also acts on +ssRNA viruses, which results in further under-representation of CpG in the vertebrate-infecting RT viruses.

An RNA folding motif: GNRA tetraloop-receptor interactions

Nearly two decades after Westhof and Michel first proposed that RNA tetraloops may interact with distal helices, tetraloop–receptor interactions have been recognized as ubiquitous elements of RNA tertiary structure. The unique architecture of GNRA tetraloops (N=any nucleotide, R=purine) enables interaction with a variety of receptors, e.g., helical minor grooves and asymmetric internal loops. The most common example of the latter is the GAAA tetraloop–11 nt tetraloop receptor motif. Biophysical characterization of this motif provided evidence for the modularity of RNA structure, with applications spanning improved crystallization methods to RNA tectonics. In this review, we identify and compare types of GNRA tetraloop–receptor interactions. Then we explore the abundance of structural, kinetic, and thermodynamic information on the frequently occurring and most widely studied GAAA tetraloop–11 nt receptor motif. Studies of this interaction have revealed powerful paradigms for structural assembly of RNA, as well as providing new insights into the roles of cations, transition states and protein chaperones in RNA folding pathways. However, further research will clearly be necessary to characterize other tetraloop–receptor and long-range tertiary binding interactions in detail – an important milestone in the quantitative prediction of free energy landscapes for RNA folding.

PKscan: a program to identify H-type RNA pseudoknots in any RNA sequence with unlimited length

A computer program written in C++ has been developed which can detect all potential H-type RNA pseudoknots within any given RNA sequence. There is no limit on the length of the input sequence. A validation run of the program using the full-length (8173 nt) genomic mRNA of simian retrovirus type-1 (SRV-1) identifies the established -1 frameshift stimulating pseudokont at the gagpro junction as the most stable pseudoknot within the genomic mRNA.

The long-range P3 helix of the Tetrahymena ribozyme is disrupted during folding between the native and misfolded conformations

RNAs are prone to misfolding, but how misfolded structures are formed and resolved remains incompletely understood. The Tetrahymena group I intron ribozyme folds in vitro to a long-lived misfolded conformation (M) that includes extensive native structure but is proposed to differ in topology from the native state (N). A leading model predicts that exchange of the topologies requires unwinding of the long-range, core helix P3, despite the presence of P3 in both conformations. To test this model, we constructed 16 mutations to strengthen or weaken P3. Catalytic activity and in-line probing showed that nearly all of the mutants form the M state before folding to N. The P3-weakening mutations accelerated refolding from M (3- to 30-fold) and the P3-strengthening mutations slowed refolding (6- to 1400-fold), suggesting that P3 indeed unwinds transiently. Upon depletion of Mg(2+), the mutations had analogous effects on unfolding from N to intermediates that subsequently fold to M. The magnitudes for the P3-weakening mutations were larger than in refolding from M, and small-angle X-ray scattering showed that the ribozyme expands rapidly to intermediates from which P3 is disrupted subsequently. These results are consistent with previous results indicating unfolding of native peripheral structure during refolding from M, which probably permits rearrangement of the core. Together, our results demonstrate that exchange of the native and misfolded conformations requires loss of a core helix in addition to peripheral structure. Further, the results strongly suggest that misfolding arises from a topological error within the ribozyme core, and a specific topology is proposed.

The essential role of stacking adenines in a two-base-pair RNA kissing complex

In minimal RNA kissing complexes formed between hairpins with cognate GACG tetraloops, the two tertiary GC pairs are likely stabilized by the stacking of 5'-unpaired adenines at each end of the short helix. To test this hypothesis, we mutated the flanking adenines to various nucleosides and examined their effects on the kissing interaction. Electrospray ionization mass spectrometry was used to detect kissing dimers in a multiequilibria mixture, whereas optical tweezers were applied to monitor the (un)folding trajectories of single RNA molecules. The experimental findings were rationalized by molecular dynamics simulations. Together, the results showed that the stacked adenines are indispensable for the tertiary interaction. By shielding the tertiary base pairs from solvent and reducing their fraying, the stacked adenines made terminal pairs act more like interior base pairs. The purine double-ring of adenine was essential for effective stacking, whereas additional functional groups modulated the stabilizing effects through varying hydrophobic and electrostatic forces. Furthermore, formation of the kissing complex was dominated by base pairing, whereas its dissociation was significantly influenced by the flanking bases. Together, these findings indicate that unpaired flanking nucleotides play essential roles in the formation of otherwise unstable two-base-pair RNA tertiary interactions.

Ion-mediated RNA structural collapse: effect of spatial confinement

RNAs are negatively charged molecules that reside in cellular environments with macromolecular crowding. Macromolecular confinement can influence the ion effects in RNA folding. In this work, using the recently developed tightly bound ion model for ion fluctuation and correlation, we investigate the effect of confinement on ion-mediated RNA structural collapse for a simple model system. We find that for both Na(+) and Mg(2+), the ion efficiencies in mediating structural collapse/folding are significantly enhanced by the structural confinement. This enhancement of ion efficiency is attributed to the decreased electrostatic free-energy difference between the compact conformation ensemble and the (restricted) extended conformation ensemble due to the spatial restriction.

Predicting kissing interactions in microRNA-target complex and assessment of microRNA activity

MicroRNAs (miRNAs) are a class of short RNA molecules that play an important role in post-transcriptional gene regulation. Computational prediction of the miRNA target sites in mRNA is crucial for understanding the mechanism of miRNA-mRNA interactions. We here develop a new computational model that allows us to treat a variety of miRNA-mRNA kissing interactions, which have been ignored in the currently existing miRNA target prediction algorithms. By including all the different inter- and intra-molecular base pairs, this new model can predict both the structural accessibility of the target sites and the binding affinity (free energy). Applications of the model to a test set of 105 miRNA-gene systems show a notably improved success rate of 83/105. We found that although the binding affinity alone predicts the miRNA repression efficiency with a high success rate of 73/105, the structure in the seed region can significantly influence the miRNA activity. The method also allows us to efficiently search for the potent miRNA from a pool of miRNA candidates for any given gene target. Furthermore, extension of the method may enable predictions of the three-dimensional (3D) structures of miRNA/mRNA complexes.

Predicting ion-nucleic acid interactions by energy landscape-guided sampling

The recently developed Tightly Bound Ion (TBI) model offers improved predictions for ion effect in nucleic acid systems by accounting for ion correlation and fluctuation effects. However, further application of the model to larger systems is limited by the low computational efficiency of the model. Here, we develop a new computational efficient TBI model using free energy landscape-guided sampling method. The method leads to drastic reduction in the computer time by a factor of 50 for RNAs of 50-100 nucleotides long. The improvement in the computational efficiency would be more significant for larger structures. To test the new method, we apply the model to predict the free energies and the number of bound ions for a series of RNA folding systems. The validity of this new model is supported by the nearly exact agreement with the results from the original TBI model and the agreement with the experimental data. The method may pave the way for further applications of the TBI model to treat a broad range of biologically significant systems such as tetraloop-receptor and riboswitches.

Dominant role of the 5' TAR bulge in dimerization of HIV-1 genomic RNA, but no evidence of TAR-TAR kissing during in vivo virus assembly

The 5' untranslated region of HIV-1 genomic RNA (gRNA) contains two stem-loop structures that appear to be equally important for gRNA dimerization: the 57-nucleotide 5' TAR, at the very 5' end, and the 35-nucleotide SL1 (nucleotides 243-277). SL1 is well-known for containing the dimerization initiation site (DIS) in its apical loop. The DIS is a six-nucleotide palindrome. Here, we investigated the mechanism of TAR-directed gRNA dimerization. We found that the trinucleotide bulge (UCU24) of the 5' TAR has dominant impacts on both formation of HIV-1 RNA dimers and maturation of the formed dimers. The ΔUCU trinucleotide deletion strongly inhibited the first process and blocked the other, thus impairing gRNA dimerization as severely as deletion of the entire 5' TAR, and more severely than deletion of the DIS, inactivation of the viral protease, or most severe mutations in the nucleocapsid protein. The apical loop of TAR contains a 10-nucleotide palindrome that has been postulated to stimulate gRNA dimerization by a TAR-TAR kissing mechanism analogous to the one used by SL1 to stimulate dimerization. Using mutations that strongly destabilize formation of the TAR palindrome duplex, as well as compensatory mutations that restore duplex formation to a wild-type-like level, we found no evidence of TAR-TAR kissing, even though mutations nullifying the kissing potential of the TAR palindrome could impair dimerization by a mechanism other than hindering of SL1. However, nullifying the kissing potential of TAR had much less severe effects than ΔUCU. By not uncovering a dimerization mechanism intrinsic to TAR, our data suggest that TAR mutations exert their effect 3' of TAR, yet not on SL1, because TAR and SL1 mutations have synergistic effects on gRNA dimerization.

Statistical mechanical modeling of RNA folding: from free energy landscape to tertiary structural prediction

In spite of the success of computational methods for predicting RNA secondary structure, the problem of predicting RNA tertiary structure folding remains. Low-resolution structural models show promise as they allow for rigorous statistical mechanical computation for the conformational entropies, free energies, and the coarse-grained structures of tertiary folds. Molecular dynamics refinement of coarse-grained structures leads to all-atom 3D structures. Modeling based on statistical mechanics principles also has the unique advantage of predicting the full free energy landscape, including local minima and the global free energy minimum. The energy landscapes combined with the 3D structures form the basis for quantitative predictions of RNA functions. In this chapter, we present an overview of statistical mechanical models for RNA folding and then focus on a recently developed RNA statistical mechanical model -- the Vfold model. The main emphasis is placed on the physics underpinning the models, the computational strategies, and the connections to RNA biology.

Rational truncation of an RNA aptamer to prostate-specific membrane antigen using computational structural modeling

RNA aptamers represent an emerging class of pharmaceuticals with great potential for targeted cancer diagnostics and therapy. Several RNA aptamers that bind cancer cell-surface antigens with high affinity and specificity have been described. However, their clinical potential has yet to be realized. A significant obstacle to the clinical adoption of RNA aptamers is the high cost of manufacturing long RNA sequences through chemical synthesis. Therapeutic aptamers are often truncated postselection by using a trial-and-error process, which is time consuming and inefficient. Here, we used a "rational truncation" approach guided by RNA structural prediction and protein/RNA docking algorithms that enabled us to substantially truncateA9, an RNA aptamer to prostate-specific membrane antigen (PSMA),with great potential for targeted therapeutics. This truncated PSMA aptamer (A9L; 41mer) retains binding activity, functionality, and is amenable to large-scale chemical synthesis for future clinical applications. In addition, the modeled RNA tertiary structure and protein/RNA docking predictions revealed key nucleotides within the aptamer critical for binding to PSMA and inhibiting its enzymatic activity. Finally, this work highlights the utility of existing RNA structural prediction and protein docking techniques that may be generally applicable to developing RNA aptamers optimized for therapeutic use.

Chemical correction of pre-mRNA splicing defects associated with sequestration of muscleblind-like 1 protein by expanded r(CAG)-containing transcripts

Recently, it was reported that expanded r(CAG) triplet repeats (r(CAG)(exp)) associated with untreatable neurological diseases cause pre-mRNA mis-splicing likely due to sequestration of muscleblind-like 1 (MBNL1) splicing factor. Bioactive small molecules that bind the 5'CAG/3'GAC motif found in r(CAG)(exp) hairpin structure were identified by using RNA binding studies and virtual screening/chemical similarity searching. Specifically, a benzylguanidine-containing small molecule was found to improve pre-mRNA alternative splicing of MBNL1-sensitive exons in cells expressing the toxic r(CAG)(exp). The compound was identified by first studying the binding of RNA 1 × 1 nucleotide internal loops to small molecules known to have affinity for nucleic acids. Those studies identified 4',6-diamidino-2-phenylindole (DAPI) as a specific binder to RNAs with the 5'CAG/3'GAC motif. DAPI was then used as a query molecule in a shape- and chemistry alignment-based virtual screen to identify compounds with improved properties, which identified 4-guanidinophenyl 4-guanidinobenzoate, a small molecule that improves pre-mRNA splicing defects associated with the r(CAG)(exp)-MBNL1 complex. This compound may facilitate the development of therapeutics to treat diseases caused by r(CAG)(exp) and could serve as a useful chemical tool to dissect the mechanisms of r(CAG)(exp) toxicity. The approach used in these studies, defining the small RNA motifs that bind small molecules with known affinity for nucleic acids and then using virtual screening to optimize them for bioactivity, may be generally applicable for designing small molecules that target other RNAs in the human genomic sequence.

Effects of non-nearest neighbors on the thermodynamic stability of RNA GNRA hairpin tetraloops

Currently, several models for predicting the secondary structure of RNA exist, one of which is free energy minimization using the Nearest Neighbor Model. This model predicts the lowest-free energy secondary structure from a primary sequence by summing the free energy contributions of the Watson-Crick nearest neighbor base pair combinations and any noncanonical secondary structure motif. The Nearest Neighbor Model also assumes that the free energy of the secondary structure motif is dependent solely on the identities of the nucleotides within the motif and the motif's nearest neighbors. To test the current assumption of the Nearest Neighbor Model that the non-nearest neighbors do not affect the stability of the motif, we optically melted different stem-loop oligonucleotides to experimentally determine their thermodynamic parameters. In each of these oligonucleotides, the hairpin loop sequence and the adjacent base pairs were held constant, while the first or second non-nearest neighbors were varied. The experimental results show that the thermodynamic contributions of the hairpin loop were dependent upon the identity of the first non-nearest neighbor, while the second non-nearest neighbor had a less obvious effect. These results were then used to create an updated model for predicting the thermodynamic contributions of a hairpin loop to the overall stability of the stem-loop structure.

RNA fragment modeling with a nucleobase discrete-state model

In this work we develop an approach for predicting the tertiary structures of RNA fragments by combining an RNA nucleobase discrete state (RNAnbds) model, a sequential Monte Carlo method, and a statistical potential. The RNAnbds model is designed for optimizing the configuration of nucleobases with respect to their preceding ones along the sequence and their spatial neighbors, in contrast to previous works that focus on RNA backbones. The tests of our approach with the fragments taken from a small RNA pseudoknot and a 23S ribosome RNA show that for short fragments (<10 nucleotides), the root mean square deviations (RMSDs) between the predicted and the experimental ones are generally smaller than 3 Å; for slightly longer fragments (10-15 nucleotides), most RMSDs are smaller than 4 Å. The comparison of our method with another physics-based predictor with a testing set containing nine loops shows that ours is superior in both accuracy and efficiency. Our approach is useful in facilitating RNA three-dimensional structure prediction as well as loop modeling. It also holds the promise of providing insight into the structural ensembles of RNA loops.

A domain-based model for predicting large and complex pseudoknotted structures

Pseudoknotted structures play important structural and functional roles in RNA cellular functions at the level of transcription, splicing and translation. However, the problem of computational prediction for large pseudoknotted folds remains. Here we develop a domain-based method for predicting complex and large pseudoknotted structures from RNA sequences. The model is based on the observation that large RNAs can be separated into different structural domains. The basic idea is to first identify the domains and then predict the structures for each domain. Assembly of the domain structures gives the full structure. The use of the domain-based approach leads to a reduction of computational time by a factor of about ~N ( 2) for an N-nt sequence. As applications of the model, we predict structures for a variety of RNA systems, such as regions in human telomerase RNA (hTR), internal ribosome entry site (IRES) and HIV genome. The lengths of these sequences range from 200-nt to 400-nt. The results show good agreements with the experiments.

A kinetic zipper model with intrachain interactions applied to nucleic acid hairpin folding kinetics

Single-stranded DNA and RNA hairpin structures with 4-10 nucleotides (nt) in the loop and 5-8 basepairs (bp) in the stem fold on 10-100 μs timescale. In contrast, theoretical estimate of first contact time of two ends of an ideal semiflexible polymer of similar lengths (with persistence length ~2-nt) is 10-100 ns. We propose that this three-orders-of-magnitude difference between these two timescales is a result of roughness in the folding free energy surface arising from intrachain interactions. We present a statistical mechanical model that explicitly includes all misfolded microstates with nonnative Watson-Crick (WC) and non-WC contacts. Rates of interconversion between different microstates are described in terms of two adjustable parameters: the strength of the non-WC interactions (ΔG(nWC)) and the rate at which a basepair is formed adjacent to an existing basepair (k(bp)(+)). The model accurately reproduces the temperature and loop-length dependence of the measured relaxation rates in temperature-jump studies of a 7-bp stem, single-stranded DNA hairpin with 4-20-nt-long poly(dT) loops, with ΔG(nWC) ≈ -2.4 kcal/mol and k(bp)(+) ≥ (1 ns)(-1), in 100 mM NaCl. Thus, our model provides a microscopic interpretation of the slow hairpin folding times as well as an estimate of the strength of intrachain interactions.

Analysis of RNA folding and ligand binding by conventional and high-throughput calorimetry

Noncoding RNAs serve myriad functions in the cell, but their biophysical properties are not well understood. Calorimetry offers direct and label-free means for characterizing the ligand-binding and thermostability properties of these RNA. We apply two main types of calorimetry--isothermal titration calorimetry (ITC) and differential scanning calorimetry (DSC)--to the characterization of these functional RNA molecules. ITC can describe ligand binding in terms of stoichiometry, affinity, and heat (enthalpy), while DSC can provide RNA stability in terms of heat capacity, melting temperature, and folding enthalpy. Here, we offer detailed experimental protocols for studying such RNA systems with commercially available conventional and high-throughput ITC and DSC instruments.

DNA diagnostics and exon skipping

The predominate form of DNA diagnostics remains nucleic acid sequencing in the research and clinical setting. While DNA sequencing allows a mutation to be correctly identified, only RNA sequencing can confirm the effect of that mutation on the resulting mRNA transcript. In the absence of RNA sequencing, predictions are reliant on either experimental studies or bioinformatic modelling. While each of these approaches provides insights into cellular splicing choices, of which exon skipping is but one, both possess inherent weaknesses. A method which is able to integrate and appropriately weigh the various factors influencing cellular splicing choices into an accurate, comprehensive modelling tool still remains elusive.In this overview chapter, the current methods utilised for DNA diagnostics and the impact of the emerging next-generation sequencing techniques are considered. We explore why RNA remains a problematic medium with which to work. To understand how exon skipping can be predicted from a DNA sequence, the key cis-acting elements influencing splicing are reviewed. Finally, the current methods used to predict exon skipping including RNA-based studies, experimental studies, and bioinformatic modelling approaches are outlined.

Analysis of the free energy in a stochastic RNA secondary structure model

There are two custom ways for predicting RNA secondary structures: minimizing the free energy of a conformation according to a thermodynamic model and maximizing the probability of a folding according to a stochastic model. In most cases, stochastic grammars are used for the latter alternative applying the maximum likelihood principle for determining a grammar's probabilities. In this paper, building on such a stochastic model, we will analyze the expected minimum free energy of an RNA molecule according to Turner's energy rules. Even if the parameters of our grammar are chosen with respect to structural properties of native molecules only (and therefore, independent of molecules' free energy), we prove formulae for the expected minimum free energy and the corresponding variance as functions of the molecule's size which perfectly fit the native behavior of free energies. This gives proof for a high quality of our stochastic model making it a handy tool for further investigations. In fact, the stochastic model for RNA secondary structures presented in this work has, for example, been used as the basis of a new algorithm for the (nonuniform) generation of random RNA secondary structures.

Salt contribution to RNA tertiary structure folding stability

Accurate quantification of the ionic contribution to RNA folding stability could greatly enhance our ability to understand and predict RNA functions. Recently, motivated by the potential importance of ion correlation and fluctuation in RNA folding, we developed the tightly bound ion (TBI) model. Extensive experimental tests showed that the TBI model can lead to better treatment of multivalent ions than the Poisson-Boltzmann equation. In this study, we use the model to quantify the contribution of salt (Na(+) and Mg(2+)) to the RNA tertiary structure folding free energy. Folding of the RNA tertiary structure often involves intermediates. We focus on the folding transition from an intermediate state to the native state, and compute the electrostatic folding free energy of the RNA. Based on systematic calculations for a variety of RNA molecules, we derive a set of formulas for the electrostatic free energy for tertiary structural folding as a function of the sequence length and compactness of the RNA and the Na(+) and Mg(2+) concentrations. Extensive comparisons with experimental data suggest that our model and the extracted empirical formulas are quite reliable.

Theory for RNA folding, stretching, and melting including loops and salt

Secondary structure formation of nucleic acids strongly depends on salt concentration and temperature. We develop a theory for RNA folding that correctly accounts for sequence effects, the entropic contributions associated with loop formation, and salt effects. Using an iterative expression for the partition function that neglects pseudoknots, we calculate folding free energies and minimum free energy configurations based on the experimentally derived basepairing free energies. The configurational entropy of loop formation is modeled by the asymptotic expression -clnm, where m is the length of the loop and c the loop exponent, which is an adjustable constant. Salt effects enter in two ways: first, we derive salt-induced modifications of the free energy parameters for describing basepairing, and second, we include the electrostatic free energy for loop formation. Both effects are modeled on the Debye-Hückel level including counterion condensation. We validate our theory for two different RNA sequences. For tRNA-phe, the resultant heat capacity curves for thermal denaturation at various salt concentrations accurately reproduce experimental results. For the P5ab RNA hairpin, we derive the global phase diagram in the three-dimensional space spanned by temperature, stretching force, and salt concentration and obtain good agreement with the experimentally determined critical unfolding force. We show that for a proper description of RNA melting and stretching, both salt and loop entropy effects are needed.

A conserved RNA pseudoknot in a putative molecular switch domain of the 3'-untranslated region of coronaviruses is only marginally stable

The 3'-untranslated region (UTR) of the group 2 coronavirus mouse hepatitis virus (MHV) genome contains a predicted bulged stem-loop (designated P0ab), a conserved cis-acting pseudoknot (PK), and a more distal stem-loop (designated P2). Base-pairing to create the pseudoknot-forming stem (P1(pk)) is mutually exclusive with formation of stem P0a at the base of the bulged stem-loop; as a result, the two structures cannot be present simultaneously. Herein, we use thermodynamic methods to evaluate the ability of individual subdomains of the 3' UTR to adopt a pseudoknotted conformation. We find that an RNA capable of forming only the predicted PK (58 nt; 3' nucleotides 241-185) adopts the P2 stem-loop with little evidence for P1(pk) pairing in 0.1 M KCl and the absence of Mg(2+); as Mg(2+) or 1 M KCl is added, a new thermal unfolding transition is induced and assignable to P1(pk) pairing. The P1(pk) helix is only marginally stable, ΔG(25) ≈ 1.2 ± 0.3 kcal/mol (5.0 mM Mg(2+), 100 mM K(+)), and unfolded at 37°C. Similar findings characterize an RNA 5' extended through the P0b helix only (89 nt; 294-185). In contrast, an RNA capable of forming either the P0a helix or the pseudoknot (97 nt; 301-185) forms no P1(pk) helix. Thermal unfolding simulations are fully consistent with these experimental findings. These data reveal that the PK forms weakly and only when the competing double-hairpin structure cannot form; in the UTR RNA, the double hairpin is the predominant conformer under all solution conditions.

The Azoarcus group I intron ribozyme misfolds and is accelerated for refolding by ATP-dependent RNA chaperone proteins

Structured RNAs traverse complex energy landscapes that include valleys representing misfolded intermediates. In Neurospora crassa and Saccharomyces cerevisiae, efficient splicing of mitochondrial group I and II introns requires the DEAD box proteins CYT-19 and Mss116p, respectively, which promote folding transitions and function as general RNA chaperones. To test the generality of RNA misfolding and the activities of DEAD box proteins in vitro, here we measure native folding of a small group I intron ribozyme from the bacterium Azoarcus by monitoring its catalytic activity. To develop this assay, we first measure cleavage of an oligonucleotide substrate by the prefolded ribozyme. Substrate cleavage is rate-limited by binding and is readily reversible, with an internal equilibrium near unity, such that the amount of product observed is less than the amount of native ribozyme. We use this assay to show that approximately half of the ribozyme folds readily to the native state, whereas the other half forms an intermediate that transitions slowly to the native state. This folding transition is accelerated by urea and increased temperature and slowed by increased Mg(2+) concentration, suggesting that the intermediate is misfolded and must undergo transient unfolding during refolding to the native state. CYT-19 and Mss116p accelerate refolding in an ATP-dependent manner, presumably by disrupting structure in the intermediate. These results highlight the tendency of RNAs to misfold, underscore the roles of CYT-19 and Mss116p as general RNA chaperones, and identify a refolding transition for further dissection of the roles of DEAD box proteins in RNA folding.

On the observable transition to living matter

In recent developments in chemistry and genetic engineering, the humble researcher dealing with the origin of life finds her(him)self in a grey area of tackling something that even does not yet have a clear definition agreed upon. A series of chemical steps is described to be considered as the life–nonlife transition, if one adheres to the minimalistic definition: life is self-reproduction with variations. The fully artificial RNA system chosen for the exploration corresponds sequence-wise to the reconstructed initial triplet repeats, presumably corresponding to the earliest protein-coding molecules. The demonstrated occurrence of the mismatches (variations) in otherwise complementary syntheses (“self-reproduction”), in this RNA system, opens an experimental and conceptual perspective to explore the origin of life (and its definition), on the apparent edge of the origin.

Variables and strategies in development of therapeutic post-transcriptional gene silencing agents

Post-transcriptional gene silencing (PTGS) agents such as ribozymes, RNAi and antisense have substantial potential for gene therapy of human retinal degenerations. These technologies are used to knockdown a specific target RNA and its cognate protein. The disease target mRNA may be a mutant mRNA causing an autosomal dominant retinal degeneration or a normal mRNA that is overexpressed in certain diseases. All PTGS technologies depend upon the initial critical annealing event of the PTGS ligand to the target RNA. This event requires that the PTGS agent is in a conformational state able to support hybridization and that the target have a large and accessible single-stranded platform to allow rapid annealing, although such platforms are rare. We address the biocomplexity that currently limits PTGS therapeutic development with particular emphasis on biophysical variables that influence cellular performance. We address the different strategies that can be used for development of PTGS agents intended for therapeutic translation. These issues apply generally to the development of PTGS agents for retinal, ocular, or systemic diseases. This review should assist the interested reader to rapidly appreciate critical variables in PTGS development and facilitate initial design and testing of such agents against new targets of clinical interest.

Re-engineering multicloning sites for function and convenience

Multicloning sites (MCSs) in standard expression vectors are widely used and thought to be benign, non-interacting elements that exist for mere convenience. However, MCSs impose a necessary distance between promoter elements and genes of interest. As a result, the choice of cloning site defines the genetic context and may introduce significant mRNA secondary structure in the 5′-untranslated region leading to strong translation inhibition. Here, we demonstrate the first performance-based assessment of MCSs in yeast, showing that commonly used MCSs can induce dramatic reductions in protein expression, and that this inhibition is highly promoter and gene dependent. In response, we develop and apply a novel predictive model of structure-based translation inhibition to design improved MCSs for significantly higher and more consistent protein expression. In doing so, we were able to minimize the inhibitory effects of MCSs with the yeast TEF, CYC and GPD promoters. These results highlight the non-interchangeable nature of biological parts and represent the first complete, global redesign of a genetic circuit of such widespread importance as a multicloning site. The improved translational control offered by these designed MCSs is paramount to obtaining high titers of heterologous proteins in eukaryotes and to enabling precise control of genetic circuits.

Physics-based de novo prediction of RNA 3D structures

Current experiments on structural determination cannot keep up the pace with the steadily emerging RNA sequences and new functions. This underscores the request for an accurate model for RNA three-dimensional (3D) structural prediction. Although considerable progress has been made in mechanistic studies, accurate prediction for RNA tertiary folding from sequence remains an unsolved problem. The first and most important requirement for the prediction of RNA structure from physical principles is an accurate free energy model. A recently developed three-vector virtual bond-based RNA folding model ("Vfold") has allowed us to compute the chain entropy and predict folding free energies and structures for RNA secondary structures and simple pseudoknots. Here we develop a free energy-based method to predict larger more complex RNA tertiary folds. The approach is based on a multiscaling strategy: from the nucleotide sequence, we predict the two-dimensional (2D) structures (defined by the base pairs and tertiary contacts); based on the 2D structure, we construct a 3D scaffold; with the 3D scaffold as the initial state, we combine AMBER energy minimization and PDB-based fragment search to predict the all-atom structure. A key advantage of the approach is the statistical mechanical calculation for the conformational entropy of RNA structures, including those with cross-linked loops. Benchmark tests show that the model leads to significant improvements in RNA 3D structure prediction.

NUPACK: Analysis and design of nucleic acid systems

The Nucleic Acid Package (NUPACK) is a growing software suite for the analysis and design of nucleic acid systems. The NUPACK web server (http://www.nupack.org) currently enables:

ANALYSIS

thermodynamic analysis of dilute solutions of interacting nucleic acid strands.

DESIGN

sequence design for complexes of nucleic acid strands intended to adopt a target secondary structure at equilibrium.Utilities: evaluation, display, and annotation of equilibrium properties of a complex of nucleic acid strands. NUPACK algorithms are formulated in terms of nucleic acid secondary structure. In most cases, pseudoknots are excluded from the structural ensemble.

Predicting ion binding properties for RNA tertiary structures

Recent experiments pointed to the potential importance of ion correlation for multivalent ions such as Mg(2+) ions in RNA folding. In this study, we develop an all-atom model to predict the ion electrostatics in RNA folding. The model can treat ion correlation effects explicitly by considering an ensemble of discrete ion distributions. In contrast to the previous coarse-grained models that can treat ion correlation, this new model is based on all-atom nucleic acid structures. Thus, unlike the previous coarse-grained models, this new model allows us to treat complex tertiary structures such as HIV-1 DIS type RNA kissing complexes. Theory-experiment comparisons for a variety of tertiary structures indicate that the model gives improved predictions over the Poisson-Boltzmann theory, which underestimates the Mg(2+) binding in the competition with Na(+). Further systematic theory-experiment comparisons for a series of tertiary structures lead to a set of analytical formulas for Mg(2+)/Na(+) ion-binding to various RNA and DNA structures over a wide range of Mg(2+) and Na(+) concentrations.

Roles of DEAD-box proteins in RNA and RNP Folding

RNAs and RNA-protein complexes (RNPs) traverse rugged energy landscapes as they fold to their native structures, and many continue to undergo conformational rearrangements as they function. Due to the inherent stability of local RNA structure, proteins are required to assist with RNA conformational transitions during initial folding and in exchange between functional structures. DEAD-box proteins are superfamily 2 RNA helicases that are ubiquitously involved in RNA-mediated processes. Some of these proteins use an ATP-dependent cycle of conformational changes to disrupt RNA structure nonprocessively, accelerating structural transitions of RNAs and RNPs in a manner that bears a strong resemblance to the activities of certain groups of protein chaperones. This review summarizes recent work using model substrates and tractable self-splicing intron RNAs, which has given new insights into how DEAD-box proteins promote RNA folding steps and conformational transitions, and it summarizes recent progress in identifying sites and mechanisms of DEAD-box protein activity within more complex cellular targets.

Folding kinetics for the conformational switch between alternative RNA structures

Transitions between different conformational states, so-called conformational switching, are intrinsic to RNA catalytic and regulatory functions. Often, conformational switching occurs on time scales of several seconds. In combination with the recent real-time NMR experiments (Wenter et al. Angew. Chem. Int. Ed. 2005, 44, 2600; Wenter et al. ChemBioChem 2006, 7, 417) for the transitions between bistable RNA conformations, we combine the master equation method with the kinetic cluster method to investigate the detailed kinetic mechanism and the factors that govern the folding kinetics. We propose that heat capacity change (ΔC(p)) upon RNA folding may be important for RNA folding kinetics. In addition, we find that, for tetraloop hairpins, noncanonical (tertiary) intraloop interactions are important to determine the folding kinetics. Furthermore, through theory-experiment comparisons, we find that the different rate models for the fundamental steps (i.e., formation/disruption of a base pair or stack) can cause contrasting results in the theoretical predictions.

Computing the conformational entropy for RNA folds

We develop a polymer physics-based method to compute the conformational entropy for RNA tertiary folds, namely, conformations consisting of multiple helices connected through (cross-linked) loops. The theory is based on a virtual bond conformational model for the nucleotide chain. A key issue in the calculation of the entropy is how to treat the excluded volume interactions. The weak excluded volume interference between the different loops leads to the decomposition of the whole structure into a number of three-body building blocks, each consisting of a loop and two helices connected to the two ends of the loop. The simple construct of the three-body system allows an accurate computation for the conformational entropy for each building block. The assembly of the building blocks gives the entropy of the whole structure. This approach enables treatment of molten globule-like folds (partially unfolded tertiary structures) for RNAs. Extensive tests against experiments and exact computer enumerations indicate that the method can give accurate results for the entropy. The method developed here provides a solid first step toward a systematic development of a theory for the entropy and free energy landscape for complex tertiary folds for RNAs and proteins.

Nucleic acid sequence design via efficient ensemble defect optimization

We describe an algorithm for designing the sequence of one or more interacting nucleic acid strands intended to adopt a target secondary structure at equilibrium. Sequence design is formulated as an optimization problem with the goal of reducing the ensemble defect below a user-specified stop condition. For a candidate sequence and a given target secondary structure, the ensemble defect is the average number of incorrectly paired nucleotides at equilibrium evaluated over the ensemble of unpseudoknotted secondary structures. To reduce the computational cost of accepting or rejecting mutations to a random initial sequence, candidate mutations are evaluated on the leaf nodes of a tree-decomposition of the target structure. During leaf optimization, defect-weighted mutation sampling is used to select each candidate mutation position with probability proportional to its contribution to the ensemble defect of the leaf. As subsequences are merged moving up the tree, emergent structural defects resulting from crosstalk between sibling sequences are eliminated via reoptimization within the defective subtree starting from new random subsequences. Using a Θ(N(3) ) dynamic program to evaluate the ensemble defect of a target structure with N nucleotides, this hierarchical approach implies an asymptotic optimality bound on design time: for sufficiently large N, the cost of sequence design is bounded below by 4/3 the cost of a single evaluation of the ensemble defect for the full sequence. Hence, the design algorithm has time complexity Ω(N(3) ). For target structures containing N ∈{100,200,400,800,1600,3200} nucleotides and duplex stems ranging from 1 to 30 base pairs, RNA sequence designs at 37°C typically succeed in satisfying a stop condition with ensemble defect less than N/100. Empirically, the sequence design algorithm exhibits asymptotic optimality and the exponent in the time complexity bound is sharp.

Prediction of RNA multiloop and pseudoknot conformations from a lattice-based, coarse-grain tertiary structure model

We present a semiquantitative lattice model of RNA folding, which is able to reproduce complex folded structures such as multiloops and pseudoknots without relying on the frequently employed ad hoc generalization of the Jacobson-Stockmayer loop entropy. We derive the model parameters from the Turner description of simple secondary structural elements and pay particular attention to the unification of mismatch and coaxial stacking parameters as well as of border and nonlocal loop parameters, resulting in a reduced, unified parameter set for simple loops of arbitrary type and size. For elementary structures, the predictive power of the model is comparable to the standard secondary structure approaches, from which its parameters are derived. For complex structures, our approach offers a systematic treatment of generic effects of chain connectivity as well as of excluded volume or attractive interactions between and within all elements of the secondary structure. We reproduce the native structures of tRNA multiloops and of viral frameshift signal pseudoknots.

SHAPE-directed RNA secondary structure prediction

The diverse functional roles of RNA are determined by its underlying structure. Accurate and comprehensive knowledge of RNA structure would inform a broader understanding of RNA biology and facilitate exploiting RNA as a biotechnological tool and therapeutic target. Determining the pattern of base pairing, or secondary structure, of RNA is a first step in these endeavors. Advances in experimental, computational, and comparative analysis approaches for analyzing secondary structure have yielded accurate structures for many small RNAs, but only a few large (>500 nts) RNAs. In addition, most current methods for determining a secondary structure require considerable effort, analytical expertise, and technical ingenuity. In this review, we outline an efficient strategy for developing accurate secondary structure models for RNAs of arbitrary length. This approach melds structural information obtained using SHAPE chemistry with structure prediction using nearest-neighbor rules and the dynamic programming algorithm implemented in the RNAstructure program. Prediction accuracies reach >or=95% for RNAs on the kilobase scale. This approach facilitates both development of new models and refinement of existing RNA structure models, which we illustrate using the Gag-Pol frameshift element in an HIV-1 M-group genome. Most promisingly, integrated experimental and computational refinement brings closer the ultimate goal of efficiently and accurately establishing the secondary structure for any RNA sequence.

Predicting secondary structural folding kinetics for nucleic acids

We report a new computational approach to the prediction of RNA secondary structure folding kinetics. In this approach, each elementary kinetic step is represented as the transformation between two secondary structures that differ by a helix. Based on the free energy landscape analysis, we identify three types of dominant pathways and the rate constants for the kinetic steps: 1), formation; 2), disruption of a helix stem; and 3), helix formation with concomitant partial melting of a competing (incompatible) helix. The third pathway, termed the tunneling pathway, is the low-barrier dominant pathway for the conversion between two incompatible helices. Comparisons with experimental data indicate that this new method is quite reliable in predicting the kinetics for RNA secondary structural folding and structural rearrangements. The approach presented here may provide a robust first step for further systematic development of a predictive theory for the folding kinetics for large RNAs.

Enthalpy-driven RNA folding: single-molecule thermodynamics of tetraloop-receptor tertiary interaction

RNA folding thermodynamics are crucial for structure prediction, which requires characterization of both enthalpic and entropic contributions of tertiary motifs to conformational stability. We explore the temperature dependence of RNA folding due to the ubiquitous GAAA tetraloop-receptor docking interaction, exploiting immobilized and freely diffusing single-molecule fluorescence resonance energy transfer (smFRET) methods. The equilibrium constant for intramolecular docking is obtained as a function of temperature (T = 21-47 degrees C), from which a van't Hoff analysis yields the enthalpy (DeltaH degrees) and entropy (DeltaS degrees) of docking. Tetraloop-receptor docking is significantly exothermic and entropically unfavorable in 1 mM MgCl(2) and 100 mM NaCl, with excellent agreement between immobilized (DeltaH degrees = -17.4 +/- 1.6 kcal/mol, and DeltaS degrees = -56.2 +/- 5.4 cal mol(-1) K(-1)) and freely diffusing (DeltaH degrees = -17.2 +/- 1.6 kcal/mol, and DeltaS degrees = -55.9 +/- 5.2 cal mol(-1) K(-1)) species. Kinetic heterogeneity in the tetraloop-receptor construct is unaffected over the temperature range investigated, indicating a large energy barrier for interconversion between the actively docking and nondocking subpopulations. Formation of the tetraloop-receptor interaction can account for approximately 60% of the DeltaH degrees and DeltaS degrees of P4-P6 domain folding in the Tetrahymena ribozyme, suggesting that it may act as a thermodynamic clamp for the domain. Comparison of the isolated tetraloop-receptor and other tertiary folding thermodynamics supports a theme that enthalpy- versus entropy-driven folding is determined by the number of hydrogen bonding and base stacking interactions.

Predicting loop-helix tertiary structural contacts in RNA pseudoknots

Tertiary interactions between loops and helical stems play critical roles in the biological function of many RNA pseudoknots. However, quantitative predictions for RNA tertiary interactions remain elusive. Here we report a statistical mechanical model for the prediction of noncanonical loop-stem base-pairing interactions in RNA pseudoknots. Central to the model is the evaluation of the conformational entropy for the pseudoknotted folds with defined loop-stem tertiary structural contacts. We develop an RNA virtual bond-based conformational model (Vfold model), which permits a rigorous computation of the conformational entropy for a given fold that contains loop-stem tertiary contacts. With the entropy parameters predicted from the Vfold model and the energy parameters for the tertiary contacts as inserted parameters, we can then predict the RNA folding thermodynamics, from which we can extract the tertiary contact thermodynamic parameters from theory-experimental comparisons. These comparisons reveal a contact enthalpy (DeltaH) of -14 kcal/mol and a contact entropy (DeltaS) of -38 cal/mol/K for a protonated C(+)*(G-C) base triple at pH 7.0, and (DeltaH = -7 kcal/mol, DeltaS = -19 cal/mol/K) for an unprotonated base triple. Tests of the model for a series of pseudoknots show good theory-experiment agreement. Based on the extracted energy parameters for the tertiary structural contacts, the model enables predictions for the structure, stability, and folding pathways for RNA pseudoknots with known or postulated loop-stem tertiary contacts from the nucleotide sequence alone.

Thermodynamic characterization of naturally occurring RNA tetraloops

Although tetraloops are one of the most frequently occurring secondary structure motifs in RNA, less than one-third of the 30 most frequently occurring RNA tetraloops have been thermodynamically characterized. Therefore, 24 stem-loop sequences containing common tetraloops were optically melted, and the thermodynamic parameters DeltaH degrees , DeltaS degrees , DeltaG degrees (37,) and T(M) for each stem-loop were determined. These new experimental values, on average, are 0.7 kcal/mol different from the values predicted for these tetraloops using the model proposed by Vecenie CJ, Morrow CV, Zyra A, Serra MJ. 2006. Biochemistry 45: 1400-1407. The data for the 24 tetraloops reported here were then combined with the data for 28 tetraloops that were published previously. A new model, independent of terminal mismatch data, was derived to predict the free energy contribution of previously unmeasured tetraloops. The average absolute difference between the measured values and the values predicted using this proposed model is 0.4 kcal/mol. This new experimental data and updated predictive model allow for more accurate calculations of the free energy of RNA stem-loops containing tetraloops and, furthermore, should allow for improved prediction of secondary structure from sequence. It was also shown that tetraloops within the sequence 5'-GCCNNNNGGC-3' are, on average, 0.6 kcal/mol more stable than the same tetraloop within the sequence 5'-GGCNNNNGCC-3'. More systemic studies are required to determine the full extent of non-nearest-neighbor effects on tetraloop stability.

DotKnot: pseudoknot prediction using the probability dot plot under a refined energy model

RNA pseudoknots are functional structure elements with key roles in viral and cellular processes. Prediction of a pseudoknotted minimum free energy structure is an NP-complete problem. Practical algorithms for RNA structure prediction including restricted classes of pseudoknots suffer from high runtime and poor accuracy for longer sequences. A heuristic approach is to search for promising pseudoknot candidates in a sequence and verify those. Afterwards, the detected pseudoknots can be further analysed using bioinformatics or laboratory techniques. We present a novel pseudoknot detection method called DotKnot that extracts stem regions from the secondary structure probability dot plot and assembles pseudoknot candidates in a constructive fashion. We evaluate pseudoknot free energies using novel parameters, which have recently become available. We show that the conventional probability dot plot makes a wide class of pseudoknots including those with bulged stems manageable in an explicit fashion. The energy parameters now become the limiting factor in pseudoknot prediction. DotKnot is an efficient method for long sequences, which finds pseudoknots with higher accuracy compared to other known prediction algorithms. DotKnot is accessible as a web server at http://dotknot.csse.uwa.edu.au.

Binding of aminoglycoside antibiotics to helix 69 of 23S rRNA

Aminoglycosides antibiotics negate dissociation and recycling of the bacterial ribosome’s subunits by binding to Helix 69 (H69) of 23S rRNA. The differential binding of various aminoglycosides to the chemically synthesized terminal domains of the Escherichia coli and human H69 has been characterized using spectroscopy, calorimetry and NMR. The unmodified E. coli H69 hairpin exhibited a significantly higher affinity for neomycin B and tobramycin than for paromomycin (K_ds = 0.3 ± 0.1, 0.2 ± 0.2 and 5.4 ± 1.1 µM, respectively). The binding of streptomycin was too weak to assess. In contrast to the E. coli H69, the human 28S rRNA H69 had a considerable decrease in affinity for the antibiotics, an important validation of the bacterial target. The three conserved pseudouridine modifications (Ψ1911, Ψ1915, Ψ1917) occurring in the loop of the E. coli H69 affected the dissociation constant, but not the stoichiometry for the binding of paromomycin (K_d = 2.6 ± 0.1 µM). G1906 and G1921, observed by NMR spectrometry, figured predominantly in the aminoglycoside binding to H69. The higher affinity of the E. coli H69 for neomycin B and tobramycin, as compared to paromomycin and streptomycin, indicates differences in the efficacy of the aminoglycosides.