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STAR3D:一种基于堆栈的RNA三维结构比对工具。

STAR3D: a stack-based RNA 3D structural alignment tool.

作者信息

Ge Ping, Zhang Shaojie

机构信息

Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USA.

Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816, USA

出版信息

Nucleic Acids Res. 2015 Nov 16;43(20):e137. doi: 10.1093/nar/gkv697. Epub 2015 Jul 15.

Abstract

The various roles of versatile non-coding RNAs typically require the attainment of complex high-order structures. Therefore, comparing the 3D structures of RNA molecules can yield in-depth understanding of their functional conservation and evolutionary history. Recently, many powerful tools have been developed to align RNA 3D structures. Although some methods rely on both backbone conformations and base pairing interactions, none of them consider the entire hierarchical formation of the RNA secondary structure. One of the major issues is that directly applying the algorithms of matching 2D structures to the 3D coordinates is particularly time-consuming. In this article, we propose a novel RNA 3D structural alignment tool, STAR3D, to take into full account the 2D relations between stacks without the complicated comparison of secondary structures. First, the 3D conserved stacks in the inputs are identified and then combined into a tree-like consensus. Afterward, the loop regions are compared one-to-one in accordance with their relative positions in the consensus tree. The experimental results show that the prediction of STAR3D is more accurate for both non-homologous and homologous RNAs than other state-of-the-art tools with shorter running time.

摘要

多功能非编码RNA的各种功能通常需要形成复杂的高阶结构。因此,比较RNA分子的三维结构可以深入了解它们的功能保守性和进化历史。最近,已经开发了许多强大的工具来比对RNA三维结构。尽管有些方法既依赖于主链构象又依赖于碱基配对相互作用,但它们都没有考虑RNA二级结构的整个层次形成。一个主要问题是直接将二维结构匹配算法应用于三维坐标特别耗时。在本文中,我们提出了一种新颖的RNA三维结构比对工具STAR3D,以充分考虑堆叠之间的二维关系,而无需对二级结构进行复杂的比较。首先,识别输入中的三维保守堆叠,然后将其组合成树状的共有结构。之后,根据它们在共有树中的相对位置对环区域进行一对一比较。实验结果表明,与其他现有最先进工具相比,STAR3D对非同源和同源RNA的预测都更准确,且运行时间更短。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de67/4787758/2271cb448a26/gkv697fig1.jpg

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