Comparative Analysis of RNA Secondary Structure Accuracy on Predicted RNA 3D Models

RNA structure is conformationally dynamic, and an all-atom accurate tertiary (3D) structure modeling of RNA remains challenging with the prevailing tools. Secondary structure (2D) information is the standard prerequisite for most RNA 3D modeling. Despite several 2D and 3D structure prediction tools proposed in recent years, one of the challenges is to choose the possibly best combination for accurate RNA 3D structure prediction. Here, we have benchmarked seven small RNA PDB structures (40 to 90 nucleotides) with different topologies to understand the effect of different 2D structure predictions on the quality of 3D modeling accuracies. The current study explores the blind challenge of 2D to 3D conversions and highlights the performances of de novo RNA 3D modeling from their predicted 2D structure constraints. Our results show conformational sampling-based methods such as SimRNA and IsRNA1 depend less on 2D accuracy, whereas motif-based methods account for 2D evidence. Our observations exemplify the disparities in available 3D and 2D prediction methods and may further offer insights into developing topology or family-specific RNA structure prediction pipelines. ### Competing Interest Statement The authors have declared no competing interest.