VfoldCPX Server: Predicting RNA-RNA Complex Structure and Stability

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

The success rate of coarse-grained correct loop/junction structure predictions for (A) all the 8452 RNA loops/junctions in <i>TEST-I</i>, (B) the 7459 RNA loops and junctions in <i>TEST-II</i>, and (C) the 1119 RNA loops and junctions in <i>TEST-III</i>.

<p>The “Top-” in x-axis means that the “correct” structure is in the top lowest-potential conformations. In each figure, and represent the success rate with and , respectively.</p

Comparison between the “true” statistical potentials obtained from the RNA09 dataset and the Leontis dataset, respectively.

<p> The figures from (A) to (I) stand for the torsion angles (,  = ): (A) (, ), (B) (, ), (C) (, ), (D) (, ), (E) (, ), (F) (, ), (G) (, ), (H) (, ) and (I) (, ), respectively. In each figure, the red bars represent the statistical potentials extracted from the Leontis dataset, the green bars represent the ones from the RNA09 dataset, and the x-axis stands for the dinucleotides with different nucleotides (,  = ) AA, AC, AG, AU, CA, CC, CG, CU, GA, GC, GG, GU, UA, UC, UG and UU from 1 to 16.</p

() The RMSD between the PDB structures and the diamond lattice-represented structures for RNA loops and junctions in the RNA09 dataset.

<p> The x-axis represents the index of RNA loops/junctions in the RNA09 dataset. () The number of RNA loops/junctions within each RMSD-value bin (0.1 Å). The mean and standard deviation of RMSD values for the 152 RNA loops/junctions are 1.35 Å and 0.30 Å, respectively.</p

The density plot for the base pairing probabilities, the predicted stable structures, and the density plot for the free energy landscapes for T4–35 pseudoknot at different temperatures

<p><b>Copyright information:</b></p><p>Taken from "Predicting RNA pseudoknot folding thermodynamics"</p><p>Nucleic Acids Research 2006;34(9):2634-2652.</p><p>Published online 18 May 2006</p><p>PMCID:PMC1463895.</p><p>© The Author 2006. Published by Oxford University Press. All rights reserved</p> In the free energy landscape F(, ), darker color means lower free energy. and denote the numbers of the native and the non-native base pairs, respectively. At T = 70°C, the partially unfolded pseudoknot structure (Z) coexists with the hairpin structure (X)

Quantifying Coulombic and Solvent Polarization-Mediated Forces Between DNA Helices

One of the fundamental problems in nucleic acids biophysics is to predict the different forces that stabilize nucleic acid tertiary folds. Here we provide a quantitative estimation and analysis for the forces between DNA helices in an ionic solution. Using the generalized Born model and the improved atomistic tightly binding ions model, we evaluate ion correlation and solvent polarization effects in interhelix interactions. The results suggest that hydration, Coulomb correlation and ion entropy act together to cause the repulsion and attraction between nucleic acid helices in Mg²⁺ and Mn²⁺ solutions, respectively. The theoretical predictions are consistent with experimental findings. Detailed analysis further suggests that solvent polarization and ion correlation both are crucial for the interhelix interactions. The theory presented here may provide a useful framework for systematic and quantitative predictions of the forces in nucleic acids folding

A snapshot of the output of the VfoldCPX server. Based on the total length of the input effective one-RNA system, the server provides up to three sets of predicted structures, corresponding to the three structural ensembles shown in Fig 2(B).

<p>In this example, the predicted most probable 2D structure (plotted using VARNA [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0163454#pone.0163454.ref035" target="_blank">35</a>]) has the free energy of -50.24 kcal/mol. The predicted base pairing distributions shown by the density plot and the alternative stable structures provide important information about the structures and stabilities.</p

Comparison between the “extracted” statistical potentials from the RNA09 dataset and the Leontis dataset, respectively.

<p> The figures from (A) to (I) stand for the torsion angles (,  = ): (A) (, ), (B) (, ), (C) (, ), (D) (, ), (E) (, ), (F) (, ), (G) (, ), (H) (, ) and (I) (, ), respectively. In each figure, the red bars represent the statistical potentials extracted from the Leontis dataset, the green bars represent the ones from the RNA09 dataset, and the x-axis stands for the dinucleotides with different nucleotides (,  = ) AA, AC, AG, AU, CA, CC, CG, CU, GA, GC, GG, GU, UA, UC, UG and UU from 1 to 16.</p

Comparison between the “extracted” statistical potentials and the “true” potentials .

<p>The figures from (A) to (I) stand for the torsion angles (,  = ): (A) (, ), (B) (, ), (C) (, ), (D) (, ), (E) (, ), (F) (, ), (G) (, ), (H) (, ) and (I) (, ), respectively. In each figure, the red bars represent the statistical potentials , the green bars represent the statistical potentials , both of which are obtained from the RNA09 dataset, and the x-axis stands for the dinucleotides with different nucleotides (,  = ) AA, AC, AG, AU, CA, CC, CG, CU, GA, GC, GG, GU, UA, UC, UG and UU from 1 to 16.</p

IsRNA: An Iterative Simulated Reference State Approach to Modeling Correlated Interactions in RNA Folding

Coarse-grained RNA folding models promise great potential for RNA structure prediction. A key component in a coarse-grained folding model is the force field. One of the challenges in the coarse-grained force field calculation is how to treat the correlation between the different degrees of freedoms. Here, we describe a new approach (IsRNA) to extract the correlated energy functions from the known structures. Through iterative molecular dynamics simulations, we build the correlation effects into the reference states, from which we extract the energy functions. The validity of IsRNA is supported by the close agreement between the simulated Boltzmann-like probability distributions for all the structure parameters and those observed from the experimentally determined structures. The correlated energy functions derived here may provide a new tool for RNA 3D structure prediction