Xu Xiaojun, Chen Shi-Jie
Department of Physics, University of Missouri, Columbia, MO, 65211, USA.
Methods Mol Biol. 2015;1316:1-11. doi: 10.1007/978-1-4939-2730-2_1.
The ever increasing discoveries of noncoding RNA functions draw a strong demand for RNA structure determination from the sequence. In recently years, computational studies for RNA structures, at both the two-dimensional and the three-dimensional levels, led to several highly promising new developments. In this chapter, we describe a recently developed RNA structure prediction method based on the virtual bond-based coarse-grained folding model (Vfold). The main emphasis in the Vfold method is placed on the loop entropy calculations, the treatment of noncanonical (mismatch) interactions and the 3D structure assembly from motif-based template library. As case studies, we use the glycine riboswitch and the G310-U376 domain of MLV RNA to illustrate the Vfold-based prediction of RNA 3D structures from the sequences.
非编码RNA功能的发现日益增多,这使得从序列确定RNA结构的需求愈发强烈。近年来,针对RNA结构的二维和三维层面的计算研究带来了一些极具前景的新进展。在本章中,我们描述了一种基于虚拟键粗粒度折叠模型(Vfold)的最新开发的RNA结构预测方法。Vfold方法的主要重点在于环熵计算、非规范(错配)相互作用的处理以及基于基序的模板库进行三维结构组装。作为案例研究,我们使用甘氨酸核糖开关和莫洛尼氏白血病病毒(MLV)RNA的G310-U376结构域来说明基于Vfold从序列预测RNA三维结构的方法。