RNA structural insights through prediction and probing
This review explores methods for predicting RNA secondary structures by integrating reactivity information from experimental probing data. It highlights the limitations of traditional RNA structure prediction, which typically relies solely on thermodynamic models based on sequences
We discuss how experimental techniques for chemical and enzymatic structure probing like SHAPE or PARS can provide valuable insights into RNA structure, allowing for more accurate predictions when combined with thermodynamics-only algorithms. By incorporating probing data as soft constraints or pseudo-energies in folding algorithms, we can enhance the accuracy of RNA structure models. The paper also addresses the challenges of merging these approaches and outlines future directions for improving RNA structure determination through the integration of experimental and computational methods.
Citation
Predicting RNA Structures from Sequence and Probing Data
Ronny Lorenz, Michael T. Wolfinger, Andrea Tanzer, Ivo L. Hofacker
Methods 103:86–98 (2016) | doi:10.1016/j.ymeth.2016.04.004 | PDF
See Also
SHAPE Directed RNA Folding
Ronny Lorenz, Dominik Luntzer, Ivo L. Hofacker, Peter F. Stadler, Michael T. Wolfinger
Bioinformatics 32: 145–47 (2016) | doi:10.1093/bioinformatics/btv523 | PDF