A Hitchhiker's guide to RNA-RNA structure and interaction prediction tools

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Noncoding RNAs (ncRNAs) have emerged as critical regulators in human cells, mediating diverse functions through interactions with other RNAs.
• These RNA-RNA interactions (RRIs) are fundamental to processes like genetic translation, RNA splicing, and metabolic regulation.
• The vastness of the human genome and advances in experimental techniques necessitate sophisticated computational tools for analyzing the RNA interactome.

Approach:

• This review provides an update on computational tools for RNA-RNA interaction (RRI) analysis, focusing on thermodynamic and comparative methods for RNA secondary structure prediction (RSP) and RNA-RNA interaction prediction (RIP).
• It examines the current understanding of RRIs and the limitations of experimental RNA interactome mapping.
• Key aspects discussed include the gap between RSP and RIP, the significance of RNA homologues, pseudoknot structures, and RNA folding thermodynamics.

Key Points:

• Computational tools are essential for analyzing the increasing volume of RNA interaction data.
• Understanding RRIs is crucial for deciphering complex cellular functions and genomic regulation.
• Experimental limitations in RNA interactome mapping highlight the need for robust predictive algorithms.

Conclusions:

• Emerging prediction tools for RRIs promise to enhance our comprehension of RNA's role in human diseases.
• Improved RRI analysis can accelerate the development of therapeutic strategies targeting RNA-associated conditions.
• Further development in prediction algorithms will bridge the gap between RNA structure prediction and interaction prediction.