IsRNAcirc: 3D structure prediction of circular RNAs based on coarse-grained molecular dynamics simulation

Area of Science:

• Computational biology
• Molecular biology
• RNA structure prediction

Background:

• Circular RNAs are an emerging class of molecules with significant biological roles.
• Understanding the three-dimensional (3D) structure of circular RNAs is essential for elucidating their functions.
• Predicting circular RNA 3D structures presents challenges due to their flexibility and length.

Purpose of the Study:

• To introduce IsRNAcirc, a novel computational method for predicting circular RNA 3D structures.
• To enhance the accuracy and reliability of circular RNA structure prediction.
• To provide a tool for exploring the structural details and interactions of circular RNAs.

Main Methods:

• IsRNAcirc extends the IsRNA2 model using coarse-grained molecular dynamics simulations.
• The workflow involves input preparation, end closure, structure prediction, and model refinement.
• The method addresses challenges posed by circular RNA flexibility and length.

Main Results:

• IsRNAcirc generates reasonable 3D structure predictions for circular RNAs.
• The method effectively reduces irrational elements in initial structural models.
• IsRNAcirc outperformed the template-based 3dRNA method on a validation set of 34 circular RNAs.

Conclusions:

• IsRNAcirc is a promising computational tool for circular RNA 3D structure prediction.
• The method aids in understanding the structural basis of circular RNA biological significance.
• IsRNAcirc facilitates the exploration of intricate circular RNA interactions.