> ## Documentation Index
> Fetch the complete documentation index at: https://proto.evodesign.org/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# ViennaRNA
> First released in 1994, ViennaRNA is a thermodynamic RNA secondary-structure prediction package. From an RNA or DNA sequence it computes the minimum-free-energy secondary structure and its free energy using a nearest-neighbor energy model, with no training and no GPU required. It is widely used to predict and compare the base-pairing of messenger RNAs, non-coding RNAs, riboswitches, and designed RNA constructs.
**License:** ViennaRNA is licensed under Custom (ViennaRNA Package License) and may require explicit attribution when utilized. Please refer to [the license](https://github.com/ViennaRNA/ViennaRNA/blob/master/COPYING) for full terms.
Proto is not affiliated with TBI Vienna. This toolkit is open source and builds on the implementation produced by this organization. Product names, logos, and trademarks are the property of their respective owners.
```bibtex theme={null}
@article{lorenz2011viennarna,
title={ViennaRNA Package 2.0},
author={Lorenz, Ronny and Bernhart, Stephan H and H{\"o}ner zu Siederdissen, Christian and Tafer, Hakim and Flamm, Christoph and Stadler, Peter F and Hofacker, Ivo L},
journal={Algorithms for Molecular Biology},
volume={6},
number={1},
pages={26},
year={2011},
publisher={BioMed Central},
doi={10.1186/1748-7188-6-26}
}
```
| Function | Description | |
| ----------------- | -------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `run_viennarna()` | RNA secondary structure prediction using ViennaRNA MFE folding | Docs Source |
## Background
ViennaRNA ([Lorenz et al., 2011](https://doi.org/10.1186/1748-7188-6-26)) predicts the secondary structure of a nucleic-acid sequence: the set of intramolecular base pairs that form within a single strand. Secondary structure sits between sequence and three-dimensional shape and governs how many functional RNAs behave, so predicting it from sequence alone is a core step in RNA analysis and design.
Internally, ViennaRNA folds each sequence with the minimum-free-energy dynamic program at the core of RNAfold (cubic in the sequence length) under a nearest-neighbor thermodynamic model. RNA sequences use the Turner 2004 parameters. Selecting the DNA option instead loads the Mathews 2004 DNA parameters. The predicted structure is returned in dot-bracket notation together with its minimum free energy in kcal/mol, where a more negative value indicates a more stable predicted fold. Because it is a thermodynamic rather than a learned method, it is deterministic, runs on CPU, and predicts secondary structure only, not three-dimensional coordinates.
The reference implementation is the ViennaRNA Package, maintained by [TBI Vienna](https://www.tbi.univie.ac.at/) at [ViennaRNA/ViennaRNA](https://github.com/ViennaRNA/ViennaRNA).
### Learning Resources
* [ViennaRNA Package documentation and tutorials](https://www.tbi.univie.ac.at/RNA/) (TBI Vienna) - the official documentation, worked tutorials, and the RNAfold web server for trying predictions interactively.
## Tools
### ViennaRNA Secondary Structure Prediction (`viennarna-prediction`)
Folds each input sequence to its minimum-free-energy secondary structure, returning the structure in dot-bracket notation and the minimum free energy in kcal/mol for every sequence.
#### API Reference
Source
RNA (A, U, G, C), DNA (A, T, G, C), or N sequences to fold (any case). T is converted to U before folding unless DNA parameters are used.
Source
Temperature in Celsius for energy calculations.
Use DNA energy parameters instead of RNA parameters.
Disallow lonely base pairs (helices of length 1).
Dangling-end treatment (0=ignore, 1=minimal, 2=multibranch, 3=accurate).
Available options: `0`, `1`, `2`, `3`
Treat sequence as circular (plasmids, viroids, circRNAs).
Max base-pair span in nt; -1 = no limit, positive forbids long-range pairs.
Verbosity level (0=quiet, 1=info, 2=debug, 3=raw subprocess stderr). `True` is coerced to `1` and `False` to `0`.
Device to run the tool on.
Maximum execution time in seconds. `None` waits indefinitely.
Random seed. When set, tools run reproducibly up to small GPU float noise (see `BaseToolOutput.approx_equal`), and the seed participates in cache keys. When None, cacheable seed-sensitive tools skip cache until seeded.
Source
List of fold results, one per input sequence. Each result contains the sequence, predicted structure in dot-bracket notation, and the minimum free energy.
The input RNA sequence.
Predicted secondary structure in dot-bracket notation.
Minimum free energy in kcal/mol.
#### Applications
Use this to predict the base-pairing of mRNAs, non-coding RNAs, riboswitches, aptamers, or designed RNA constructs from sequence alone, for example to check whether a designed UTR or guide RNA folds as intended, or to rank candidate sequences by the stability of their predicted fold.
#### Usage Tips
* **`temperature` (default `37.0`, degrees Celsius) sets the folding temperature.** The energy model is temperature-dependent, so the predicted structure and free energy change with it. Keep the default for physiological predictions and change it to model other conditions.
* **`use_dna_params` (default `False`) also changes how the input is read.** When `False`, any `T` in a sequence is converted to `U` and the sequence is folded as RNA with the Turner 2004 parameters. Set it `True` to fold the sequence as DNA with the Mathews 2004 DNA parameters and no `T`-to-`U` conversion.
* **Set `circ` to `True` for circular molecules.** Plasmids, viroids, and circular RNAs fold differently from linear strands, and the default treats the sequence as linear.
* **`no_lonely_pairs` (default `False`) forbids isolated base pairs.** Enabling it removes length-one helices, which often yields more physically realistic structures.
* **`dangles` (default `2`) sets dangling-end energy treatment.** Choose `0` to ignore dangling ends, `1` for minimal, `2` for multibranch, or `3` for the most accurate model.
* **`max_bp_span` (default `-1`, unlimited) caps the base-pair span.** Set a positive value to forbid long-range pairs, which is useful for very long sequences or local-structure analysis.
## Toolkit Notes
These apply to every ViennaRNA tool in this toolkit (`viennarna-prediction`).
* **Runs on CPU.** ViennaRNA is a fast C package and does not use a GPU. Folding is near-instant for typical sequences, and runtime grows as the cube of sequence length, so very long inputs are slower.
* **Predicts secondary structure only.** The output is a base-pairing pattern and a free energy, not three-dimensional atomic coordinates; use a tertiary-structure method when 3D is needed.
**Example notebook:** See the [full working example](https://github.com/evo-design/proto-tools/blob/47e34afa5ea240a3b406e323dc38aa5dc85f223e/proto_tools/tools/structure_prediction/viennarna/examples/example.ipynb) for a copy-paste-ready walkthrough.
## Infrastructure Guides
The following guides cover how to run tools efficiently and at scale.
Keep a tool's model warm across calls instead of reloading it every invocation.How GPUs are allocated to tools and how to target specific devices.Fan a batch of inputs out across multiple GPUs.
evo-design/proto-tools/proto\_tools/tools/structure\_prediction/viennarna
TBI Vienna
