Thermodynamic characterization of naturally occurring RNA pentaloops.

RNA folding is hierarchical; therefore, predicting RNA secondary structure from sequence is an intermediate step in predicting tertiary structure. Secondary structure prediction is based on a nearest neighbor model using free energy minimization. To improve secondary structure prediction, all types of naturally occurring secondary structure motifs need to be thermodynamically characterized. However, not all secondary structure motifs are well characterized. Pentaloops, the second most abundant hairpin size, is one such uncharacterized motif. In fact, the current thermodynamic model used to predict the stability of pentaloops was derived from a small data set of pentaloops and from data for other hairpins of different sizes. Here, the most commonly occurring pentaloops were identified and optically melted. New experimental data for 22 pentaloop sequences were combined with previously published data for nine pentaloop sequences. Using linear regression, a pentaloop-specific model was derived. This new model is simpler and more accurate than the current model. The new experimental data and improved model can be incorporated into software that is used to predict RNA secondary structure from sequence.

Thermodynamic determination of RNA duplex stability in magnesium solutions.

The prediction of RNA secondary structure and thermodynamics from sequence relies on free energy minimization and nearest neighbor parameters. Currently, algorithms used to make these predictions are based on parameters from optical melting studies performed in 1 M NaCl. However, many physiological and biochemical buffers containing RNA include much lower concentrations of monovalent cations and the presence of divalent cations. In order to improve these algorithms, thermodynamic data was previously collected for RNA duplexes in solutions containing 71, 121, 221, and 621 mM Na+. From this data, correction factors for free energy (ΔG°37) and melting temperature (Tm) were derived. Despite these newly derived correction factors for sodium, the stabilizing effects of magnesium have been ignored. Here, the same RNA duplexes were melted in solutions containing 0.5, 1.5, 3.0, and 10.0 mM Mg2+ in the absence of monovalent cations. Correction factors for Tm and ΔG°37 were derived to scale the current parameters to a range of magnesium concentrations. The Tm correction factor predicts the melting temperature within 1.2°C, and the ΔG°37 correction factor predicts the free energy within 0.30 kcalmol. These newly derived magnesium correction factors can be incorporated into algorithms that predict RNA secondary structure and stability from sequence.

Predictions and analyses of RNA nearest neighbor parameters for modified nucleotides.

The most popular RNA secondary structure prediction programs utilize free energy (ΔG°37) minimization and rely upon thermodynamic parameters from the nearest neighbor (NN) model. Experimental parameters are derived from a series of optical melting experiments; however, acquiring enough melt data to derive accurate NN parameters with modified base pairs is expensive and time consuming. Given the multitude of known natural modifications and the continuing use and development of unnatural nucleotides, experimentally characterizing all modified NNs is impractical. This dilemma necessitates a computational model that can predict NN thermodynamics where experimental data is scarce or absent. Here, we present a combined molecular dynamics/quantum mechanics protocol that accurately predicts experimental NN ΔG°37 parameters for modified nucleotides with neighboring Watson-Crick base pairs. NN predictions for Watson-Crick and modified base pairs yielded an overall RMSD of 0.32 kcal/mol when compared with experimentally derived parameters. NN predictions involving modified bases without experimental parameters (N6-methyladenosine, 2-aminopurineriboside, and 5-methylcytidine) demonstrated promising agreement with available experimental melt data. This procedure not only yields accurate NN ΔG°37 predictions but also quantifies stacking and hydrogen bonding differences between modified NNs and their canonical counterparts, allowing investigators to identify energetic differences and providing insight into sources of (de)stabilization from nucleotide modifications.

Thermodynamic characterization and nearest neighbor parameters for RNA duplexes under molecular crowding conditions.

It is essential to study RNA under molecular crowding conditions to better predict secondary structures of RNAs in vivo. No systematic study has been completed to determine the effects of molecular crowding on RNA duplexes of varying lengths and sequence composition. Here, optical melting, circular dichroism, and osmometry data were collected for RNA duplexes in a 20% polyethylene glycol (with an average molecular weight of 200 g/mol) solution (PEG 200), and nearest neighbor parameters were derived using this data. RNA duplexes are destabilized, on average, 1.02 kcal/mol in the presence of 20% PEG 200. The ΔG°37 values predicted by the nearest neighbor parameters for RNA duplexes in 20% PEG 200 were ∼0.65 kcal/mol closer to experimental ΔG°37 values than those predicted by the standard nearest neighbor model. For one DNA sequence in solution with small crowders, the ΔG°37 values predicted by the 20% PEG 200 RNA nearest neighbor parameters were closer to the experimental values than ΔG°37 values predicted by either the RNA or DNA standard nearest neighbor models. This indicates that the nearest neighbor parameters for RNA duplexes in 20% PEG 200 may be generalizable to RNA and DNA duplexes in solutions with small crowding agents.

Stability of RNA duplexes containing inosine·cytosine pairs.

Inosine is found naturally in the anticodon loop of tRNA, is a product of adenosine deaminases that act on RNA, and can be used in oligonucleotide probes or to investigate the role of the exocyclic amino group of guanosine. Although the thermodynamics of I·U pairs in RNA have been systematically studied [Wright, D. J., Rice, J. L., Yanker, D. M., and Znosko, B. M. (2007) Biochemistry 46, 4625-4634], the thermodynamics of I·C pairs in RNA have not. Here, we have performed optical melting experiments on a series of RNA duplexes containing I·C pairs and compared their thermodynamics to the same duplexes containing A·C and G-C pairs. Nearest neighbor parameters for single I·C pairs adjacent to Watson-Crick pairs were derived. The derived nearest neighbor parameters are compared to those previously predicted blindly through a reweighting of energy-function collection with conformational ensemble sampling in Rosetta [Chou, F.-C., Kladwang, W., Kappel, K., and Das, R. (2016) Proc. Natl. Acad. Sci. U.S.A. 113, 8430-8435]. Scientists can use these nearest neighbor parameters to calculate the stability of ADAR products and to calculate the stability of an RNA duplex in which G-to-I substitution was used to determine the role of the exocyclic amino group of G.

Identification and Characterization of New RNA Tetraloop Sequence Families.

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

The loss of a hydrogen bond: Thermodynamic contributions of a non-standard nucleotide.

Non-standard nucleotides are ubiquitous in RNA. Thermodynamic studies with RNA duplexes containing non-standard nucleotides, whether incorporated naturally or chemically, can provide insight into the stability of Watson­Crick pairs and the role of specific functional groups in stabilizing a Watson­Crick pair. For example, an A-U, inosine•U and pseudouridine•A pair each form two hydrogen bonds. However, an RNA duplex containing a central I•U pair or central Ψ•A pair is 2.4 kcal/mol less stable or 1.7 kcal/mol more stable, respectively, than the corresponding duplex containing an A-U pair. In the non-standard nucleotide purine, hydrogen replaces the exocyclic amino group of A. This replacement results in a P•U pair containing only one hydrogen bond. Optical melting studies were performed with RNA duplexes containing P•U pairs adjacent to different nearest neighbors. The resulting thermodynamic parameters were compared to RNA duplexes containing A-U pairs in order to determine the contribution of the hydrogen bond involving the exocyclic amino group. Results indicate a loss of 1.78 kcal/mol, on average, when an internal P•U replaces A-U in an RNA duplex. This value is compared to the thermodynamics of a hydrogen bond determined by similar methods. Nearest neighbor parameters were derived for use in free energy and secondary structure prediction software.

Replacing salt correction factors with optimized RNA nearest-neighbour enthalpy and entropy parameters.

We calculate the nearest-neighbour enthalpies and entropies at 5 salt concentrations of 18 RNA sequences, each for at least 9 different species concentrations, totalling 757 melting temperatures, using a melting temperature optimization method. These new parameters do not need to be salt-corrected and are shown to provide overall improved melting temperature predictions. They show a marked quadratic dependence with salt concentrations which are compensated to form linear Gibbs free energies. Two different parameter schemes were tested, with fixed or variable initial parameters. We have found that using variable initial parameters provides better predictive results than using salt correction factors and that the prediction uncertainty is considerably reduced for a validation set of independent sequences. An interpolation scheme is introduced to generate model parameters for arbitrary salt concentrations which performs better against a validation set than predictions using salt corrections.

Surprising Sequence Effects on GU Closure of Symmetric 2 × 2 Nucleotide RNA Internal Loops.

GU base pairs are important RNA structural motifs and often close loops. Accurate prediction of RNA structures relies upon understanding the interactions determining structure. The thermodynamics of some 2 × 2 nucleotide internal loops closed by GU pairs are not well understood. Here, several self-complementary oligonucleotide sequences expected to form duplexes with 2 × 2 nucleotide internal loops closed by GU pairs were investigated. Surprisingly, nuclear magnetic resonance revealed that many of the sequences exist in equilibrium between hairpin and duplex conformations. This equilibrium is not observed with loops closed by Watson-Crick pairs. To measure the thermodynamics of some 2 × 2 nucleotide internal loops closed by GU pairs, non-self-complementary sequences that preclude formation of hairpins were designed. The measured thermodynamics indicate that some internal loops closed by GU pairs are unusually unstable. This instability accounts for the observed equilibria between duplex and hairpin conformations. Moreover, it suggests that future three-dimensional structures of loops closed by GU pairs may reveal interactions that unexpectedly destabilize folding.

Nearest-neighbor parameters for 7-deaza-adenosine·uridine base pairs in RNA duplexes.

One of the major limitations in RNA structure prediction is the lack of information about the effect of nonstandard nucleotides on stability. The nonstandard nucleotide 7-deaza-adenosine (7DA) is a naturally occurring analog of adenosine that has been studied for medicinal purposes and is commonly referred to as tubercidin. In 7DA, the nitrogen in the 7 position of adenosine is replaced by a carbon. Differences in RNA duplex stability due to the removal of this nitrogen can be attributed to a possible change in hydration and a difference in base stacking interactions resulting from changes in the electrostatics of the ring. In order to determine how 7DA affects the stability of RNA, optical melting experiments were conducted on RNA duplexes that contain either internal or terminal 7DA·U pairs with all possible nearest-neighbor combinations. On average, duplexes containing 7DA·U pairs are 0.43 and 0.07 kcal/mol less stable than what is predicted for the same duplex containing internal and terminal A-U pairs, respectively. Thermodynamic parameters for all nearest-neighbor combinations of 7DA·U pairs were derived from the data. These parameters can be used to more accurately predict the secondary structure and stability of RNA duplexes containing 7DA·U pairs.

Analysis of secondary structural elements in human microRNA hairpin precursors.

BACKGROUND: MicroRNAs (miRNAs) regulate gene expression by targeting complementary mRNAs for destruction or translational repression. Aberrant expression of miRNAs has been associated with various diseases including cancer, thus making them interesting therapeutic targets. The composite of secondary structural elements that comprise miRNAs could aid the design of small molecules that modulate their function. RESULTS: We analyzed the secondary structural elements, or motifs, present in all human miRNA hairpin precursors and compared them to highly expressed human RNAs with known structures and other RNAs from various organisms. Amongst human miRNAs, there are 3808 are unique motifs, many residing in processing sites. Further, we identified motifs in miRNAs that are not present in other highly expressed human RNAs, desirable targets for small molecules. MiRNA motifs were incorporated into a searchable database that is freely available. We also analyzed the most frequently occurring bulges and internal loops for each RNA class and found that the smallest loops possible prevail. However, the distribution of loops and the preferred closing base pairs were unique to each class. CONCLUSIONS: Collectively, we have completed a broad survey of motifs found in human miRNA precursors, highly expressed human RNAs, and RNAs from other organisms. Interestingly, unique motifs were identified in human miRNA processing sites, binding to which could inhibit miRNA maturation and hence function.

Improved Model for Predicting the Free Energy Contribution of Dinucleotide Bulges to RNA Duplex Stability.

Predicting the secondary structure of RNA is an intermediate in predicting RNA three-dimensional structure. Commonly, determining RNA secondary structure from sequence uses free energy minimization and nearest neighbor parameters. Current algorithms utilize a sequence-independent model to predict free energy contributions of dinucleotide bulges. To determine if a sequence-dependent model would be more accurate, short RNA duplexes containing dinucleotide bulges with different sequences and nearest neighbor combinations were optically melted to derive thermodynamic parameters. These data suggested energy contributions of dinucleotide bulges were sequence-dependent, and a sequence-dependent model was derived. This model assigns free energy penalties based on the identity of nucleotides in the bulge (3.06 kcal/mol for two purines, 2.93 kcal/mol for two pyrimidines, 2.71 kcal/mol for 5'-purine-pyrimidine-3', and 2.41 kcal/mol for 5'-pyrimidine-purine-3'). The predictive model also includes a 0.45 kcal/mol penalty for an A-U pair adjacent to the bulge and a -0.28 kcal/mol bonus for a G-U pair adjacent to the bulge. The new sequence-dependent model results in predicted values within, on average, 0.17 kcal/mol of experimental values, a significant improvement over the sequence-independent model. This model and new experimental values can be incorporated into algorithms that predict RNA stability and secondary structure from sequence.

Thermodynamic contribution and nearest-neighbor parameters of pseudouridine-adenosine base pairs in oligoribonucleotides.

Pseudouridine (Ψ) is the most common noncanonical nucleotide present in naturally occurring RNA and serves a variety of roles in the cell, typically appearing where structural stability is crucial to function. Ψ residues are isomerized from native uridine residues by a class of highly conserved enzymes known as pseudouridine synthases. In order to quantify the thermodynamic impact of pseudouridylation on U-A base pairs, 24 oligoribonucleotides, 16 internal and eight terminal Ψ-A oligoribonucleotides, were thermodynamically characterized via optical melting experiments. The thermodynamic parameters derived from two-state fits were used to generate linearly independent parameters for use in secondary structure prediction algorithms using the nearest-neighbor model. On average, internally pseudouridylated duplexes were 1.7 kcal/mol more stable than their U-A counterparts, and terminally pseudouridylated duplexes were 1.0 kcal/mol more stable than their U-A equivalents. Due to the fact that Ψ-A pairs maintain the same Watson-Crick hydrogen bonding capabilities as the parent U-A pair in A-form RNA, the difference in stability due to pseudouridylation was attributed to two possible sources: the novel hydrogen bonding capabilities of the newly relocated imino group as well as the novel stacking interactions afforded by the electronic configuration of the Ψ residue. The newly derived nearest-neighbor parameters for Ψ-A base pairs may be used in conjunction with other nearest-neighbor parameters for accurately predicting the most likely secondary structure of A-form RNA containing Ψ-A base pairs.

Effect of intercalator substituent and nucleotide sequence on the stability of DNA- and RNA-naphthalimide complexes.

DNA intercalators are commonly used as anti-cancer and anti-tumor agents. As a result, it is imperative to understand how changes in intercalator structure affect binding affinity to DNA. Amonafide and mitonafide, two naphthalimide derivatives that are active against HeLa and KB cells in vitro, were previously shown to intercalate into DNA. Here, a systematic study was undertaken to change the 3-substituent on the aromatic intercalator 1,8-naphthalimide to determine how 11 different functional groups with a variety of physical and electronic properties affect binding of the naphthalimide to DNA and RNA duplexes of different sequence compositions and lengths. Wavelength scans, NMR titrations, and circular dichroism were used to investigate the binding mode of 1,8-naphthalimide derivatives to short synthetic DNA. Optical melting experiments were used to measure the change in melting temperature of the DNA and RNA duplexes due to intercalation, which ranged from 0 to 19.4°C. Thermal stabilities were affected by changing the substituent, and several patterns and idiosyncrasies were identified. By systematically varying the 3-substituent, the binding strength of the same derivative to various DNA and RNA duplexes was compared. The binding strength of different derivatives to the same DNA and RNA sequences was also compared. The results of these comparisons shed light on the complexities of site specificity and binding strength in DNA-intercalator complexes. For example, the consequences of adding a 5'-TpG-3' or 5'-GpT-3' step to a duplex is dependent on the sequence composition of the duplex. When added to a poly-AT duplex, naphthalimide binding was enhanced by 5.6-11.5°C, but when added to a poly-GC duplex, naphthalimide binding was diminished by 3.2-6.9°C.

A Computational Model for Predicting Experimental RNA Nearest-Neighbor Free Energy Rankings: Inosine•Uridine Pairs.

A computational model for predicting RNA nearest neighbor free energy rankings has been expanded to include the nonstandard nucleotide inosine. The model uses average fiber diffraction data and molecular dynamic simulations to generate input geometries for Quantum mechanic calculations. This resulted in calculated intrastrand stacking, interstrand stacking, and hydrogen bonding energies that were combined to give total binding energies. Total binding energies for RNA dimer duplexes containing inosine were ranked and compared to experimentally determined free energy ranks for RNA duplexes containing inosine. Statistical analysis showed significant agreement between the computationally determined ranks and the experimentally determined ranks.

Improved model to predict the free energy contribution of trinucleotide bulges to RNA duplex stability.

Trinucleotide bulges in RNA commonly occur in nature. Yet, little data exists concerning the thermodynamic parameters of this motif. Algorithms that predict RNA secondary structure from sequence currently attribute a constant free energy value of 3.2 kcal/mol to all trinucleotide bulges, regardless of bulge sequence. To test the accuracy of this model, RNA duplexes that contain frequent naturally occurring trinucleotide bulges were optically melted, and their thermodynamic parameters-enthalpy, entropy, free energy, and melting temperature-were determined. The thermodynamic data were used to derive a new model to predict the free energy contribution of trinucleotide bulges to RNA duplex stability: ΔG°37, trint bulge = ΔG°37, bulge + ΔG°37, AU + ΔG°37, GU. The parameter ΔG°37, bulge is variable depending upon the purine and pyrimidine composition of the bulge, ΔG°37, AU is a 0.49 kcal/mol penalty for an A-U closing pair, and ΔG° 37, GU is a -0.56 kcal/mol bonus for a G-U closing pair. With both closing pair and bulge sequence taken into account, this new model predicts free energy values within 0.30 kcal/mol of the experimental value. The new model can be used by algorithms that predict RNA free energies as well as algorithms that use free energy minimization to predict RNA secondary structure from sequence.

RNA CoSSMos: Characterization of Secondary Structure Motifs--a searchable database of secondary structure motifs in RNA three-dimensional structures.

RNA secondary structure is important for designing therapeutics, understanding protein-RNA binding and predicting tertiary structure of RNA. Several databases and downloadable programs exist that specialize in the three-dimensional (3D) structure of RNA, but none focus specifically on secondary structural motifs such as internal, bulge and hairpin loops. The RNA Characterization of Secondary Structure Motifs (RNA CoSSMos) database is a freely accessible and searchable online database and website of 3D characteristics of secondary structure motifs. To create the RNA CoSSMos database, 2156 Protein Data Bank (PDB) files were searched for internal, bulge and hairpin loops, and each loop's structural information, including sugar pucker, glycosidic linkage, hydrogen bonding patterns and stacking interactions, was included in the database. False positives were defined, identified and reclassified or omitted from the database to ensure the most accurate results possible. Users can search via general PDB information, experimental parameters, sequence and specific motif and by specific structural parameters in the subquery page after the initial search. Returned results for each search can be viewed individually or a complete set can be downloaded into a spreadsheet to allow for easy comparison. The RNA CoSSMos database is automatically updated weekly and is available at http://cossmos.slu.edu.

Competitive Influence of Alkali Metals in the Ion Atmosphere on Nucleic Acid Duplex Stability.

The nonspecific atmosphere around nucleic acids, often termed the ion atmosphere, encompasses a collection of weak ion-nucleic acid interactions. Although nonspecific, the ion atmosphere has been shown to influence nucleic acid folding and structural stability. Studies investigating the composition of the ion atmosphere have shown competitive occupancy of the atmosphere between metal ions in the same solution. Many studies have investigated single ion effects on nucleic acid secondary structure stability; however, no comprehensive studies have investigated how the competitive occupancy of mixed ions in the ion atmosphere influences nucleic acid secondary structure stability. Here, six oligonucleotides were optically melted in buffers containing molar quantities, or mixtures, of either XCl (X = Li, K, Rb, or Cs) or NaCl. A correction factor was developed to better predict RNA duplex stability in solutions containing mixed XCl/NaCl. For solutions containing a 1:1 mixture of XCl/NaCl, one alkali metal chloride contributed more to duplex stability than the other. Overall, there was a 54% improvement in predictive capabilities with the correction factor compared with the standard 1.0 M NaCl nearest-neighbor models. This correction factor can be used in models to better predict RNA secondary structure in solutions containing mixed XCl/NaCl.

Effect of sodium ions on RNA duplex stability.

The standard sodium concentration for RNA optical melting experiments is 1.021 M. Algorithms that predict Tm, ΔG°37, and secondary structure from sequence generally rely on parameters derived from optical melting experiments performed in 1.021 M sodium. Physiological monovalent cation concentrations are much lower than 1.021 M. In fact, many molecular biology techniques require buffers containing monovalent cation concentrations other than 1.021 M. Predictions based on the 1.021 M Na(+) parameters may not be accurate when the monovalent cation concentration is not 1.021 M. Here, we report thermodynamic data from optical melting experiments for a set of 18 RNA duplexes, each melted over a wide range of sodium ion concentrations (71, 121, 221, and 621 mM). Using these data and previously published data for the same sequences melted in 1.021 M Na(+), we report Tm and ΔG°37 correction factors to scale the standard 1.021 M Na(+) RNA parameters to other sodium ion concentrations. The recommended Tm correction factor predicts the melting temperature within 0.7 °C, and the recommended ΔG°37 correction factor predicts the free energy within 0.14 kcal/mol. These correction factors can be incorporated into prediction algorithms that predict RNA secondary structure from sequence and provide Tm and ΔG°37 values for RNA duplexes.

Structural characterization of naturally occurring RNA single mismatches.

RNA is known to be involved in several cellular processes; however, it is only active when it is folded into its correct 3D conformation. The folding, bending and twisting of an RNA molecule is dependent upon the multitude of canonical and non-canonical secondary structure motifs. These motifs contribute to the structural complexity of RNA but also serve important integral biological functions, such as serving as recognition and binding sites for other biomolecules or small ligands. One of the most prevalent types of RNA secondary structure motifs are single mismatches, which occur when two canonical pairs are separated by a single non-canonical pair. To determine sequence-structure relationships and to identify structural patterns, we have systematically located, annotated and compared all available occurrences of the 30 most frequently occurring single mismatch-nearest neighbor sequence combinations found in experimentally determined 3D structures of RNA-containing molecules deposited into the Protein Data Bank. Hydrogen bonding, stacking and interaction of nucleotide edges for the mismatched and nearest neighbor base pairs are described and compared, allowing for the identification of several structural patterns. Such a database and comparison will allow researchers to gain insight into the structural features of unstudied sequences and to quickly look-up studied sequences.