Prof. Dan Barash

Computational RNA design was introduced in the 1990s by Vienna’s RNAinverse, which is a simple inverse RNA folding solver. Further developments and contemporary RNA design techniques, in addition to improved efficiency, offer more precise control over the designed sequences. incaRNAfbinv (incaRNAtion with RNA fragment-based inverse) is one such extension that builds upon RNAinverse and includes coarse-graining manipulations. The idea is that an RNA secondary structure can be decomposed to fragments of RNA motifs, and that a significant number of known natural RNA motifs exhibit a remarkable preservation in particular locations in a variety of genomes. This is taken into consideration by the ability of the user to select motifs that are known to be functional for a precise design, whilst the algorithm is more adaptable on other motifs. The latest version, incaRNAfbinv 2.0, is a free-to-use web-server which deploys the above methodology of fragment-based design. Its control over the decomposed RNA secondary structure motifs includes, among other advanced features, the insertion of constraints in a flexible manner. The resultant RNA designed sequences are ranked by their proximity to classical RNA design. Features and capabilities of incaRNAfbinv 2.0 are hereby illustrated with an example taken from hepatitis delta virus (HDV). The web-server is demonstrated in assisting to locate a known RNA motif that is responsible for HDV-3 RNA editing in more HDV genotypes than thought of before. This shows that computational RNA design by using inverse RNA folding is also a valuable strategy for locating functional RNA motifs in genomic data, in addition to artificially designing synthetic RNAs.