School of Computer Science, McGill University, 3480 University Street, Montreal, QC H3A 0E9, Canada.
Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel.
Nucleic Acids Res. 2017 Jul 3;45(W1):W440-W444. doi: 10.1093/nar/gkx429.
RNA structures are hierarchically organized. The secondary structure is articulated around sophisticated local three-dimensional (3D) motifs shaping the full 3D architecture of the molecule. Recent contributions have identified and organized recurrent local 3D motifs, but applications of this knowledge for predictive purposes is still in its infancy. We recently developed a computational framework, named RNA-MoIP, to reconcile RNA secondary structure and local 3D motif information available in databases. In this paper, we introduce a web service using our software for predicting RNA hybrid 2D-3D structures from sequence data only. Optionally, it can be used for (i) local 3D motif prediction or (ii) the refinement of user-defined secondary structures. Importantly, our web server automatically generates a script for the MC-Sym software, which can be immediately used to quickly predict all-atom RNA 3D models. The web server is available at http://rnamoip.cs.mcgill.ca.
RNA 结构具有层次组织性。二级结构围绕复杂的局部三维（3D）模体形成分子的完整 3D 结构。最近的研究成果已经确定并组织了常见的局部 3D 模体，但该知识在预测方面的应用仍处于起步阶段。我们最近开发了一种名为 RNA-MoIP 的计算框架，用于协调数据库中可用的 RNA 二级结构和局部 3D 模体信息。在本文中，我们介绍了一个使用我们的软件的网络服务，该服务仅从序列数据预测 RNA 杂交的 2D-3D 结构。它还可以选择用于（i）局部 3D 模体预测或（ii）用户定义的二级结构的细化。重要的是，我们的网络服务器会自动生成一个用于 MC-Sym 软件的脚本，该脚本可以立即用于快速预测 RNA 的全原子 3D 模型。该网络服务器可在 http://rnamoip.cs.mcgill.ca 上获得。
