Crumple: An Efficient Tool to Explore Thoroughly the RNA Folding Landscape

Area of Science:

• Computational Biology
• Structural Biology
• Bioinformatics

Background:

• RNA sequences exhibit complex folding landscapes with numerous structures.
• Complete exploration of these landscapes has been computationally challenging.
• Advancements in supercomputing enable more exhaustive analysis.

Purpose of the Study:

• To provide protocols for using the Crumple folding algorithm.
• To enable complete enumeration of non-pseudoknotted RNA folds.
• To integrate experimental constraints into RNA structure prediction.

Main Methods:

• Utilizing the Crumple folding algorithm for RNA structure enumeration.
• Employing Sliding Windows and Assembly for constraint integration.
• Independent of free-energy minimization approaches.

Main Results:

• Protocols for generating all possible non-pseudoknotted RNA folds are provided.
• The method incorporates experimental data like chemical probing and phylogenetic covariation.
• Global RNA features, such as helix number and length, can be constrained.

Conclusions:

• Complete enumeration of RNA folding landscapes is now feasible.
• The Crumple algorithm offers an efficient tool for exploring diverse RNA structures.
• Integration of experimental data enhances the accuracy of predicted RNA folds.