CopomuS-Ranking Compensatory Mutations to Guide RNA-RNA Interaction Verification Experiments.

Area of Science:

• Computational Biology
• Molecular Biology
• Bioinformatics

Background:

• In silico RNA-RNA interaction prediction identifies potential partners.
• Experimental verification often uses compensatory mutations, but selection is subjective.
• Objective criteria are needed to guide compensatory mutation selection.

Purpose of the Study:

• Introduce CopomuS, a tool to objectively select compensatory mutations for RNA-RNA interactions.
• Improve the reliability and efficiency of designing verification experiments.
• Provide a computational aid for RNA-RNA interaction studies.

Main Methods:

• Utilized the IntaRNA prediction tool for RNA-RNA interaction assessment.
• Analyzed characteristics of experimentally validated RNA-RNA interactions from literature.
• Developed CopomuS based on objective criteria derived from interaction analysis.
• Evaluated CopomuS performance using validated compensatory mutations of prokaryotic sRNAs and target mRNAs.

Main Results:

• CopomuS provides objective criteria for evaluating mutation effects on RNA-RNA interactions.
• The tool outputs a reliable ranking of compensatory mutation candidates.
• CopomuS predictions show high agreement with experimentally validated results.
• The tool is integrated into the IntaRNA package and available as a webserver.

Conclusions:

• CopomuS is a valuable tool for supporting the design of RNA-RNA interaction verification experiments.
• Objective selection of compensatory mutations enhances experimental reliability.
• The tool facilitates in silico analysis and in vitro validation of RNA interactions.