Recent advancements in RNA three-dimensional (3D) structure prediction have provided significant insights into RNA biology, highlighting the essential role of RNA in cellular functions and its therapeutic potential. This review summarizes the latest developments in computational methods, particularly the incorporation of artificial intelligence and machine learning, which have improved the efficiency and accuracy of RNA structure predictions. We also discuss the integration of new experimental data types, including cryoelectron microscopy (cryo-EM) techniques and high-throughput sequencing, which have transformed RNA structure modeling. The combination of experimental advances with computational methods represents a significant leap in RNA structure determination. We review the outcomes of RNA-Puzzles and critical assessment of structure prediction (CASP) challenges, which assess the state of the field and limitations of existing methods. Future perspectives are discussed, focusing on the impact of RNA 3D structure prediction on understanding RNA mechanisms and its implications for drug discovery and RNA-targeted therapies, opening new avenues in molecular biology.

中文翻译：

---

RNA 3D 结构预测和建模领域的进展，采用纯理论方法，并使用实验数据


RNA 三维 （3D） 结构预测的最新进展为 RNA 生物学提供了重要的见解，突出了 RNA 在细胞功能中的重要作用及其治疗潜力。本文总结了计算方法的最新发展，特别是人工智能和机器学习的结合，这些方法提高了 RNA 结构预测的效率和准确性。我们还讨论了新的实验数据类型的集成，包括冷冻电子显微镜 （cryo-EM） 技术和高通量测序，它们改变了 RNA 结构建模。实验进展与计算方法的结合代表了 RNA 结构测定的重大飞跃。我们回顾了 RNA-Puzzles 的结果和结构预测 （CASP） 挑战的批判性评估，这些挑战评估了该领域的状态和现有方法的局限性。讨论了未来的前景，重点关注 RNA 3D 结构预测对理解 RNA 机制的影响及其对药物发现和 RNA 靶向治疗的影响，为分子生物学开辟了新的途径。