cRNAsp12

cRNAsp12 predicts secondary structures and folding stabilities of circular RNAs (circRNAs) to model their structural properties relevant to function and RNA-based therapeutics.

Key Features:

• CircRNA-specific modeling: Accounts for covalently closed loop circRNAs lacking 5' and 3' ends in secondary structure prediction.
• Secondary structure prediction: Predicts secondary structures for input circRNA sequences.
• Folding stability estimation: Estimates folding stabilities of predicted structures.
• Helix-based landscape partitioning: Uses a helix-based landscape partitioning strategy to generate distinct ensembles of potential structures.
• Ensemble-specific MFE prediction: Predicts minimal free energy (MFE) structures for each ensemble.
• Partition function and backtracking: Employs recursive partition function calculations combined with backtracking algorithms to obtain MFE structures.
• Structural constraints: Allows specification of base pairs or unpaired bases that must be included or excluded from predicted structures.

Scientific Applications:

• Structural analysis of circRNAs: Characterizes secondary-structure ensembles and energetics of circRNAs for studies of their structural properties.
• Functional inference: Supports investigation of structure–function relationships of circRNAs by providing constrained and unconstrained structure predictions.
• Therapeutic development: Provides structural and stability information relevant to design and evaluation of RNA-based therapeutics targeting circRNAs.

Methodology:

Helix-based landscape partitioning generates distinct structure ensembles, for which minimal free energy (MFE) structures are predicted using recursive partition function calculations combined with backtracking; users can impose explicit base-pairing or unpaired constraints.