Related tools
RNAeval
RNAeval calculates the free energy of an RNA secondary structure for a given sequence. Evaluates if a proposed structure is thermodynamically favorable.
RNAfold
RNAfold predicts RNA secondary structure using minimum free energy (MFE) algorithms and optionally returns partition-function ensemble metrics when explicitly enabled.
RNALfold
RNALfold reports locally stable RNA secondary structures within a sliding window and returns their start and end positions on the input sequence.
RNAplfold
RNAplfold computes local base pair probabilities using a sliding window approach. Useful for analyzing accessibility and identifying binding sites in long RNA sequences.
RNAsubopt
RNAsubopt enumerates all RNA secondary structures within a specified energy range above the minimum free energy (MFE). Useful for exploring the structural ensemble and identifying alternative conformations.
ViennaRNA
ViennaRNA exposes a curated set of upstream-faithful ViennaRNA 2.7.2 workflows for RNA folding, density-of-states analysis, interaction prediction, local accessibility, plotting, inverse folding, and structure analysis.
RNAcofold
RNAcofold predicts the joint secondary structure of two interacting RNA molecules and optionally reports partition-function and concentration-dependent equilibrium metrics.
RNAdistance
RNAdistance compares RNA secondary structures using the selected upstream ViennaRNA distance representation and comparison mode.
RNAduplex
RNAduplex computes the hybridization structure between two RNA sequences. Predicts the optimal duplex formation and binding energy.
RNAplex
RNAplex predicts fast query-target RNA interactions, reporting parsed hit coordinates, structures, and energies.
What is RNAdos?
RNAdos calculates the density of states for an RNA sequence. Where most RNA folding tools return a single minimum free energy (MFE) structure, RNAdos asks a different question: for each energy level, how many distinct secondary structures exist? The result is a complete profile of the RNA's energy landscape.
This matters because the MFE structure is not always the dominant fold. An RNA molecule with thousands of alternative structures clustered near the MFE occupies a broad, flat energy landscape where no single structure dominates the ensemble. Conversely, a molecule with very few near-MFE states has a sharp, funnel-like landscape and folds reliably into its predicted structure. RNAdos quantifies this distinction directly.
Why density of states matters
The density of states connects RNA sequence to thermodynamic behavior:
- Ensemble characterization: a high state count near the MFE indicates structural promiscuity, while a low count suggests a well-defined fold
- Partition function validation: the density of states can be used to compute thermodynamic quantities (free energy, heat capacity) from first principles
- Riboswitch and regulatory RNA analysis: functional RNAs that switch between conformations often have energy landscapes with two or more competing basins, visible as peaks in the density of states at distinct energy levels
- Sequence design evaluation: when designing RNA sequences with tools like RNAinverse, the density of states reveals whether a designed sequence folds uniquely into the target structure or has many competing alternatives
How to use RNAdos online
RNAdos on ProteinIQ accepts a single RNA sequence in FASTA or plain-text format, runs the ViennaRNA RNAdos program on cloud infrastructure, and returns representative structures with per-band state counts. No local installation of the ViennaRNA package is required.
Input
| Input | Description |
|---|---|
RNA Sequence | One RNA sequence in FASTA or plain nucleotide format. RNAdos operates on a single sequence per job. |
Supported file formats: .fasta, .fa, .txt
Settings
Density-of-states options
| Setting | Type | Default | Description |
|---|---|---|---|
Maximum energy band | text | upstream default | Upper bound on the energy range for the density-of-states calculation. Leave blank to let RNAdos determine the range automatically. |
Temperature | slider (0-100) | 37 | Folding temperature in degrees Celsius. Affects thermodynamic parameter scaling. |
Salt concentration | text | upstream default | Monovalent salt concentration passed to the ViennaRNA energy model. |
Parameter file content | textarea | none | Inline ViennaRNA parameter file content. Written to a temporary file and passed via --paramFile. |
Energy parameters
| Setting | Type | Default | Description |
|---|---|---|---|
Dangling ends | select | 2 (double dangles) | Controls how unpaired nucleotides adjacent to helices contribute to the energy calculation. Mode 0 ignores them, mode 1 considers only one side, mode 2 (default) considers both sides, and mode 3 enables coaxial stacking. |
Leaving optional text fields blank preserves the upstream ViennaRNA CLI defaults.
Output
| Column | Description |
|---|---|
Sequence ID | FASTA header or auto-generated identifier |
Length (nt) | Number of nucleotides in the input sequence |
MFE (kcal/mol) | Minimum free energy of the optimal structure |
Representative Structure | Dot-bracket notation for a representative structure in each energy band |
Energy Band | The energy level (in kcal/mol above the MFE) for this row |
State Count | Number of distinct secondary structures that exist within this energy band |
Each row in the results table corresponds to one energy band. The MFE row has an energy band of 0; subsequent rows show progressively higher energy levels with their associated state counts.
Computational cost
RNAdos enumerates structures across the full energy landscape, making it the most computationally intensive ViennaRNA tool on ProteinIQ. The timeout is set to 900 seconds (15 minutes). Longer sequences or wide energy ranges increase runtime substantially. For sequences where only the MFE or partition function is needed, RNAfold is a faster alternative.