Second eigenvalue of the Laplacian matrix for predicting RNA conformational switch by mutation
Second eigenvalue of the Laplacian matrix for predicting RNA conformational switch by mutation
复制标题
DOI：
10.1093/bioinformatics/bth157
复制
发表时间：
2004-08-12
期刊：
影响因子：
5.8
通讯作者：
Barash, D
中科院分区：
文献类型：
--
作者：
Barash, D
rna的构象开关被认为在几个生物过程中具有重要的基础作用，包括翻译调控、病毒自裂调控、蛋白质生物合成和mRNA剪接。当前检测双稳定rna的方法依赖于rna组合结构空间的动力学、能量学和特性，当外部事件触发时，双稳定rna会导致结构切换。基于这些特性，已经开发出工具来预测给定序列是否折叠成以双稳定构象为特征的结构，或者通过迭代算法设计多稳定rna。一个有用的补充是，在给定初始序列的情况下，开发一个局部程序来规定驱动系统进入最佳双稳定构象所需的最小突变量。结果：我们引入了一个局部过程来预测突变，通过生成和分析特征值表，能够将野生型序列转化为双稳定构象。该方法独立于折叠算法，但依赖于它们的成功。它可以与现有工具结合使用，也可以合并到更通用的RNA预测包中。我们将此程序应用于三个经过充分研究的结构。首先，该方法在Leptomonas collosoma的剪接先导RNA中导致构象开关的突变上进行了验证，这种突变已经被实验证实。其次，该方法用于预测一种突变，该突变可导致嗜热四膜虫I组内含子核酶P5abc亚域的新构象开关。第三，将该方法应用于丁型肝炎病毒，预测将野生型转化为双稳定构象的突变，这种构象通过使用折叠预测算法计算自由能来评估。最后一个例子中的预测需要实验验证，而第一个例子中预测的突变符合实验。这支持了我们提出的方法在其他已知结构以及基因工程结构上的应用。
Conformational switching in RNAs is thought to be of fundamental importance in several biological processes, including translational regulation, regulation of self-cleavage in viruses, protein biosynthesis and mRNA splicing. Current methods for detecting bi-stable RNAs that can lead to structural switching when triggered by an outside event rely on kinetics, energetics and properties of the combinatorial structure space of RNAs. Based on these properties, tools have been developed to predict whether a given sequence folds to a structure characterized by a bi-stable conformation, or to design multi-stable RNAs by an iterative algorithm. A useful addition is in developing a local procedure to prescribe, given an initial sequence, the least amount of mutations needed to drive the system into an optimal bi-stable conformation.Results: We introduce a local procedure for predicting mutations, by generating and analyzing eigenvalue tables, that are capable of transforming the wild-type sequence into a bi-stable conformation. The method is independent of the folding algorithms but relies on their success. It can be used in conjunction with existing tools, as well as being incorporated into more general RNA prediction packages. We apply this procedure on three well-studied structures. First, the method is validated on the mutation leading to a conformational switch in the spliced leader RNA from Leptomonas collosoma, a mutation that has already been confirmed by an experiment. Second, the method is used to predict a mutation that can lead to a novel conformational switch in the P5abc subdomain of the group I intron ribozyme in Tetrahymena thermophila. Third, the method is applied on Hepatitis delta virus to predict mutations that transform the wild-type into a bi-stable conformation, a configuration assessed by calculating the free energies using folding prediction algorithms. The predictions in the final examples need to be verified experimentally, whereas the mutation predicted in the first example complies with the experiment. This supports the use of our proposed method on other known structures, as well as genetically engineered ones.