Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, MO 65211, USA.
College of Life Sciences and Institute of Quantitative Biology, Zhejiang University, Hangzhou 310058, China.
Bioinformatics. 2022 Aug 10;38(16):4042-4043. doi: 10.1093/bioinformatics/btac426.
RNA 3D structures are critical for understanding their functions and for RNA-targeted drug design. However, experimental determination of RNA 3D structures is laborious and technically challenging, leading to the huge gap between the number of sequences and the availability of RNA structures. Therefore, the computer-aided structure prediction of RNA 3D structures from sequences becomes a highly desirable solution to this problem. Here, we present a pipeline server for RNA 3D structure prediction from sequences that integrates the Vfold2D, Vfold3D and VfoldLA programs. The Vfold2D program can incorporate the SHAPE experimental data in 2D structure prediction. The pipeline can also automatically extract 2D structural constraints from the Rfam database. Furthermore, with a significantly expanded 3D template database for various motifs, this Vfold-Pipeline server can efficiently return accurate 3D structure predictions or reliable initial 3D structures for further refinement.
http://rna.physics.missouri.edu/vfoldPipeline/index.html. The data underlying this article have been provided in the article and in its online supplementary material.
Supplementary data are available at Bioinformatics online.
RNA 的三维结构对于理解其功能和针对 RNA 的药物设计至关重要。然而，RNA 三维结构的实验测定既费力又具有技术挑战性，导致序列数量与 RNA 结构可用性之间存在巨大差距。因此，从序列计算预测 RNA 三维结构成为解决这一问题的理想方法。在此，我们提出了一个从序列预测 RNA 三维结构的流水线服务器，该服务器集成了 Vfold2D、Vfold3D 和 VfoldLA 程序。Vfold2D 程序可以在二维结构预测中纳入 SHAPE 实验数据。该流水线还可以自动从 Rfam 数据库中提取二维结构约束。此外，通过为各种基序扩展了显著的 3D 模板数据库，该 Vfold-Pipeline 服务器可以高效地返回准确的 3D 结构预测或可靠的初始 3D 结构，以进行进一步细化。
http://rna.physics.missouri.edu/vfoldPipeline/index.html。本文中的数据已在文章及其在线补充材料中提供。
补充数据可在生物信息学在线获取。
