In this article, some software/tools are mentioned that are most widely used for RNA secondary structure prediction.
1. mfold
mfold is the most widely used tool for RNA secondary structure prediction based on thermodynamic methods [1]. The mfold software is freely accessible and can be downloaded from here. mfold is currently available for Unix, Linux, and Mac OS. A webserver for mfold can be accessed here. However, it has been replaced by UNAfold that is much easier to install and run. UNAfold provides additional computing parameters and can be downloaded from here.
2. RNAfold
It predicts the secondary structure of RNAs with a limit to 75oo nucleotides for partition function prediction and 10,000 nucleotides for minimum free energy predictions. The webserver of RNAfold can be freely accessed at http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/RNAfold.cgi. The minimum free energy structure prediction is based on a loop-based energy model and a dynamic programming algorithm. The energy minimized RNA structure is predicted according to the given energy parameter set and temperature [2].
3. RNAstructure
RNAstructure predicts RNA and DNA secondary structures based on different algorithms. It also provides additional features including biomolecular structure prediction, base-pairing probabilities, and equilibrium binding affinities prediction [3]. The latest version of RNAstructure Version6.2 is available to download here after filling out a registration form. It comes with a graphical user interface and command-line interface for Windows, Linux, and Mac OSs.
4. SPOT-RNA
SPOT-RNA uses an ensemble of deep neural networks and transfer learning for RNA secondary structure prediction [4]. It is completely based on machine learning. A limitation of SPOT-RNA is that it is trained by short RNAs (<500 nucleotides). But the reported prediction accuracy is high on the tested data [4]. SPOT-RNA web server can be accessed here. The source code can be downloaded from GitHub.
5. RNAsoft
RNAsoft is a collection of RNA structure prediction algorithms and design [5]. It offers several online webservers for secondary structure prediction and RNA design. These web servers offer to predict RNA secondary structure using different algorithms, lowest minimum free energy, and pseudoknots [5]. It can be easily accessed here.
References
- Zuker, M. (2003). Mfold web server for nucleic acid folding and hybridization prediction. Nucleic acids research, 31(13), 3406-3415.
- Lorenz, R., Bernhart, S. H., Zu Siederdissen, C. H., Tafer, H., Flamm, C., Stadler, P. F., & Hofacker, I. L. (2011). ViennaRNA Package 2.0. Algorithms for molecular biology, 6(1), 26.
- Reuter, J. S., & Mathews, D. H. (2010). RNAstructure: software for RNA secondary structure prediction and analysis. BMC bioinformatics, 11(1), 1-9.
- Singh, J., Hanson, J., Paliwal, K., & Zhou, Y. (2019). RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning. Nature communications, 10(1), 1-13.
- Andronescu, M., Aguirre-Hernandez, R., Condon, A., & Hoos, H. H. (2003). RNAsoft: a suite of RNA secondary structure prediction and design software tools. Nucleic acids research, 31(13), 3416-3422.
