Predicting Cotranscriptional Folding Kinetics For Riboswitch.

Area of Science:

• Computational Biology
• Molecular Biology
• Biophysics

Background:

• RNA folding is crucial for gene regulation and function.
• Cotranscriptional folding, occurring during RNA synthesis, presents unique kinetic challenges.
• Predicting these dynamic processes requires sophisticated computational models.

Purpose of the Study:

• To develop a novel helix-based transition rate model for sampling cotranscriptional RNA conformational ensembles.
• To predict cotranscriptional folding kinetics and pathways accurately.
• To provide a new computational tool for understanding RNA folding dynamics.

Main Methods:

• Development of a helix-based transition rate model.
• Application of the model to E. coli Signal Recognition Particle (SRP) RNA and pbuE riboswitch.
• Comparison of model predictions with experimental data, including SHAPE-seq and single-molecule pulling experiments.

Main Results:

• The model reliably predicts cotranscriptional folding pathways and population kinetics for E. coli SRP RNA, aligning with SHAPE-seq data.
• For the pbuE riboswitch, the model predicts force-dependent transcriptional termination and distinct folding pathways with and without adenine.
• The model identified force-induced structural transitions and conformational switches, with residence times matching experimental observations.

Conclusions:

• The developed model offers a reliable method for predicting cotranscriptional RNA folding kinetics and pathways.
• Results provide insights into RNA functions, such as gene expression regulation by riboswitches.
• The model serves as a valuable tool for quantitative predictions in RNA biophysics and molecular biology.