Predicting RNA Scaffolds with a Hybrid Method of Vfold3D and VfoldLA

Abstract

The ever-increasing discoveries of noncoding RNA functions draw a strong demand for RNA structure determination from the sequence. In recently years, computational studies for RNA structures, at both the two-dimensional and the three-dimensional levels, led to several highly promising new developments. In this chapter, we describe a hybrid method, which combines the motif template-based Vfold3D model and the loop template-based VfoldLA model, to predict RNA 3D structures. The main emphasis is placed on the definition of motifs and loops, the treatment of no-template motifs, and the 3D structure assembly from templates of motifs and loops. For illustration, we use the ZIKV xrRNA1 as an example to show the template-based prediction of RNA 3D structures from the 2D structure. The web server for the hybrid model is freely accessible at http://rna.physics.missouri.edu/vfold3D2 .

Keywords: Secondary structural motifs; Single-stranded loops; Structure prediction; Template-assembly.

Figure 1:

The definition of (A) single-stranded loops of hairpin, helix2 and tails, and (B) secondary structural motifs of internal/bulge loops and multi-branched junctions. Double-stranded helices are represented by cylinders. The red oval shape in each helix denotes the terminal base pair attached to the loops (shown as red lines). Sequences of loops and motifs are in the format of W-W (terminal base pair) and N (unpaired nucleotide), with all loops in the 5’ → 3’ directions.

Figure 2:

The workflow of the hybrid model.

Figure 3:

The prediction of the ZIKV xrRNA1. (A) Snapshot of the server input, which indicates the RNA sequence and 2D structure in dot-bracket format, as well as other job information, such as number of clusters, RMSD cutoff for clustering, job name and email address. The input 2D structure contains five helices, one three-way junction and several single-stranded loops, with a loop-kissing helix (H4 as shown in red). (B) Snapshot of the server output, which shows the detailed job information and a JSmol applet for visualization of predicted structures. The best prediction has the RMSD of 8.5 Å, compared with the experimentally determined structure.