R&D Center, PharmCADD Co. Ltd., Dong-gu, Busan, Republic of Korea.
Department of Physics, Pukyong National University, Busan, Republic of Korea.
PLoS One. 2023 Sep 1;18(9):e0290907. doi: 10.1371/journal.pone.0290907. eCollection 2023.
RNA structure is conformationally dynamic, and accurate all-atom 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 best combination for accurate RNA 3D structure prediction. Here, we benchmarked seven small RNA PDB structures (40 to 90 nucleotides) with different topologies to understand the effects of different 2D structure predictions on the accuracy of 3D modeling. 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 that conformational sampling-based methods such as SimRNA and IsRNA1 depend less on 2D accuracy, whereas motif-based methods account for 2D evidence. Our observations illustrate the disparities in available 3D and 2D prediction methods and may further offer insights into developing topology-specific or family-specific RNA structure prediction pipelines.
RNA 结构具有构象动态性，而使用现有的工具准确地对 RNA 进行全原子三级（3D）结构建模仍然具有挑战性。二级结构（2D）信息是大多数 RNA 3D 建模的标准前提。尽管近年来提出了几种 2D 和 3D 结构预测工具，但其中一个挑战是选择最佳组合以进行准确的 RNA 3D 结构预测。在这里，我们使用不同拓扑结构的七个小 RNA PDB 结构（40 到 90 个核苷酸）进行基准测试，以了解不同的 2D 结构预测对 3D 建模准确性的影响。本研究探讨了 2D 到 3D 转换的盲目挑战，并强调了从预测的 2D 结构约束中对 RNA 3D 建模进行从头开始的性能。我们的结果表明，基于构象采样的方法（如 SimRNA 和 IsRNA1）对 2D 准确性的依赖性较小，而基于基序的方法则考虑了 2D 证据。我们的观察结果说明了可用的 3D 和 2D 预测方法之间的差异，并可能进一步为开发针对特定拓扑结构或特定家族的 RNA 结构预测管道提供思路。
