RNAinverse solves the inverse RNA folding problem: given a target secondary structure in dot-bracket notation, it designs RNA sequences that fold into that structure. Introduced in the ViennaRNA package over 20 years ago, RNAinverse was the first computational approach to RNA sequence design and remains one of the fastest methods available.
The algorithm uses an adaptive random walk that iteratively mutates a candidate sequence, evaluating each mutation by comparing the predicted minimum free energy (MFE) structure against the target. By default, the search terminates when a sequence folds exactly into the desired structure.
RNA inverse folding enables practical applications across synthetic biology and research:
ProteinIQ provides cloud-based access to RNAinverse, eliminating the need for local installation of the ViennaRNA package.
| Input | Description |
|---|---|
Target Structure | Secondary structure in dot-bracket notation. Parentheses denote base pairs: ( pairs with the corresponding ). Dots represent unpaired nucleotides. |
Structure notation example: ((((....)))) represents a stem-loop with 4 base pairs and a 4-nucleotide loop.
| Setting | Description |
|---|---|
Number of designs | How many independent sequence designs to generate (1-20, default 5). Each design starts from a different random sequence. |
Temperature | Folding temperature in Celsius (0-100, default 37). Affects thermodynamic calculations. |
RNAinverse returns a spreadsheet with one row per designed sequence:
| Column | Description |
|---|---|
Design # | Sequential number identifying each design attempt |
Designed Sequence | The RNA sequence generated by the algorithm |
Actual Structure | The MFE structure that the designed sequence folds into |
MFE (kcal/mol) | Minimum free energy of the folded structure |
Distance | Base pair distance between the actual structure and the target (0 = perfect match) |
Matches Target | Whether the designed sequence folds exactly into the target structure |
RNAinverse performs an adaptive random walk through sequence space. Starting from a random nucleotide sequence, the algorithm:
The base pair distance counts the number of base pairs that differ between two structures. A distance of zero means the designed sequence folds exactly into the target.
Not all design attempts succeed. A Distance value greater than zero indicates the algorithm could not find a sequence folding exactly into the target. This occurs more frequently with:
Multiple designs with distance zero provide sequence diversity while maintaining the target fold. These sequences can be useful for experimental studies requiring structural equivalence with sequence variation.
RNAinverse does not guarantee a solution exists for every target structure. Some structures are thermodynamically impossible to achieve as the MFE fold. If all design attempts return non-zero distances, consider whether the target structure is realistic.
The algorithm optimizes for the MFE structure only. A designed sequence might fold into the target as its MFE, but have many near-optimal alternative structures. For applications requiring a well-defined structural ensemble, verify the design using RNAsubopt to examine alternative conformations.
