Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
J Mol Biol. 2022 Jun 15;434(11):167452. doi: 10.1016/j.jmb.2022.167452. Epub 2022 Jan 13.
3D structures of RNAs are the basis for understanding their biological functions. However, experimentally solved RNA 3D structures are very limited. Therefore, many computational methods have been proposed to solve this problem, including our 3dRNA. 3dRNA is an automated template-based method of building RNA 3D structures from sequences and secondary structures by using the smallest secondary elements (SSEs) (http://biophy.hust.edu.cn/new/3dRNA). The first version of 3dRNA simply predicts an assembled structure for a target RNA. Later, it is improved to generate a set of assembled models and a method to further optimize them using experimental or theoretical restraints. In particular, pseudoknot base pairings are treated as restraints to solve the problem of no 3D templates for pseudoknots. Here 3dRNA is further extended to predict the 3D structures of circular RNAs since thousands of circular RNAs have been found recently but no 3D structures of them have been determined up to now. We show that circular RNAs can be divided into four types and two types show similar 3D structures with their linear counterparts while two types very different. We also show that the predicted structures of circular RNAs can bind to their ligands more stable than those of their linear counterparts, consistent with experimental results.
RNA 的 3D 结构是理解其生物学功能的基础。然而，实验确定的 RNA 3D 结构非常有限。因此，已经提出了许多计算方法来解决这个问题，包括我们的 3dRNA。3dRNA 是一种自动化的基于模板的方法，通过使用最小的二级元件 (SSEs)（http://biophy.hust.edu.cn/new/3dRNA）从序列和二级结构构建 RNA 3D 结构。3dRNA 的第一个版本只是简单地预测目标 RNA 的组装结构。后来，它被改进为生成一组组装模型，并使用实验或理论约束进一步优化它们的方法。特别是，假结碱基配对被视为约束条件，以解决没有假结 3D 模板的问题。这里 3dRNA 进一步扩展到预测环状 RNA 的 3D 结构，因为最近已经发现了数千个环状 RNA，但到目前为止还没有确定它们的 3D 结构。我们表明，环状 RNA 可以分为四种类型，其中两种与它们的线性对应物具有相似的 3D 结构，而另外两种则非常不同。我们还表明，环状 RNA 的预测结构比它们的线性对应物更稳定地结合它们的配体，这与实验结果一致。
