非编码RNA参与各个层次的生理活动并与多种重大疾病发生密切相关，是近年生物学的一个重大发现。确定RNA原子水平的三维空间结构是认识和理解非编码RNA多样性功能的基础。由于非编码RNA分子易于降解，实验上测定其三维空间结构非常困难，因此发展构建RNA分子三维空间结构的理论方法十分必要。现在已有一些RNA三级结构预测方法，但由于实验测定的非编码RNA三级结构的数目非常有限和RNA折叠机理不十分清楚，这些方法还有很大的局限性，精度还需要提高，特别是还不能预测长非编码RNA的三级结构。本项目组最近发展了一套预测RNA三维空间结构的方法3dRNA，预测精度高于国际上现有的方法，特别是对较长的RNA。本项目拟在此基础上，提出新的思路来解决采样、模板构建和评估函数等关键问题，进一步提高3dRNA预测精度，探索长非编码RNA三级结构的预测，为理解非编码RNA的结构和功能提供帮助。

One of the important discoveries in biology is that noncoding RNA can participate in various biological processes. To understand the diverse functions of noncoding RNAs, it is necessary to know their three-dimensional structures. However, it is difficult to measure RNA tertiary structures experimentally at present and so developing computational method to predict RNA tertiary structure is alternative approach. However，due to the limited number of the measured RNA structures and incomplete understanding of the RNA folding mechanism, existing methods of RNA tertiary structure prediction are only applicable to short RNA molecules. Recently we have proposed a novel method of three-dimensional RNA structure prediction, 3dRNA, with accuracy of higher than the existing methods, especially for larger RNA. In this proposal we plan to further improve 3dRNA to increase its accuracy by sampling, theoretical building of RNA templates and evaluation function of RNA tertiary structures and explore the way to treat long RNA molecules and hope it is helpful to the understanding of RNA structure and function.