IPANEMAP: integrative probing analysis of nucleic acids empowered by multiple accessibility profiles

Area of Science:

• Molecular Biology
• Biophysics
• Computational Biology

Background:

• Reliable RNA structure modeling is crucial for understanding RNA function.
• Manual interpretation of multiple chemical probing profiles is complex and limits reproducibility.
• Existing methods struggle to integrate diverse probing data effectively.

Purpose of the Study:

• To develop the first automated method for RNA structure modeling from multiple probing reactivity profiles.
• To improve the quality and reproducibility of RNA structure modeling.
• To enable joint analysis of diverse probing data for predicting dominant RNA conformations.

Main Methods:

• IPANEMAP combines sampling, clustering, and multi-optimization techniques.
• The method jointly analyzes reactivity profiles from diverse protocols, reagents, or variants.
• It predicts stable secondary structure models supported by experimental evidence.

Main Results:

• IPANEMAP demonstrates strong performance in modeling RNA structure from multiple probing datasets.
• The method is effective even when using a single probing dataset (mono-probing setting).
• Analysis confirms the benefits of integrating multiple sources of probing data.

Conclusions:

• IPANEMAP offers an automated and robust solution for RNA structure modeling.
• Integrating multiple probing data sources enhances model accuracy and reliability.
• The findings inform the design of more informative probing assays for RNA structure determination.