Helix-Based RNA Landscape Partition and Alternative Secondary Structure Determination

Area of Science:

• Molecular Biology
• Biophysics
• Computational Biology

Background:

• RNA molecules are dynamic and can adopt multiple conformations crucial for their function.
• Understanding the RNA folding landscape, including alternative structures, is key to deciphering RNA mechanisms.
• Existing methods may not fully capture the complexity of RNA conformational heterogeneity.

Purpose of the Study:

• To develop a novel helix-based strategy for partitioning the RNA folding landscape.
• To accurately determine alternative RNA secondary structures.
• To investigate the role of metastable states in RNA conformational dynamics and gene regulation.

Main Methods:

• A helix-based strategy was developed to analyze RNA folding.
• The method partitions the folding landscape into distinct secondary structure levels.
• It predicts representative structures for each partition and estimates equilibrium populations.

Main Results:

• The model successfully partitioned the folding landscapes of 27 benchmark RNAs with alternative stable structures.
• It accurately predicted representative secondary structures for each partition.
• For a 2'dG-sensing riboswitch, predicted structures and populations revealed transcript-length-dependent allosteric switching, aligning with experimental data.

Conclusions:

• The helix-based strategy effectively divides RNA folding landscapes and identifies alternative structures.
• Metastable RNA conformations play a significant role in gene regulation, as demonstrated by the riboswitch analysis.
• This work provides a foundation for landscape-based investigations into RNA folding mechanisms and functions.