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预测单链RNA二级结构的计算机方法。

Computer method for predicting the secondary structure of single-stranded RNA.

作者信息

Studnicka G M, Rahn G M, Cummings I W, Salser W A

出版信息

Nucleic Acids Res. 1978 Sep;5(9):3365-87. doi: 10.1093/nar/5.9.3365.

Abstract

We present a computer method utilizing published values for base pairing energies to compute the most energetically favorable secondary structure of an RNA from its primary nucleotide sequence. After listing all possible double-helical regions, every pair of mutally incompatible regions (whose nucleotides overlap) is examined to determine whether parts of those two regions can be combined by branch migration to form a pair of compatible new subregions which together are more stable than either of the original regions separately. These subregions are added to the list of base pairing regions which will compete to form the best overall structure. Then, a 'hyperstructure matrix' is generated, containing the unique topological relationship between every pair of regions. We have shown that the best structure can be chosen directly from this matrix, without the necessity of creating and examing every possible secondary structure. We have included the results from our solution of the 5S rRNA of the cyanobacterium Anacystis nidulans as an example of our program's capabilities.

摘要

我们提出了一种计算机方法,利用已发表的碱基配对能量值,根据RNA的一级核苷酸序列计算出能量上最有利的二级结构。在列出所有可能的双螺旋区域后,检查每一对相互不兼容的区域(其核苷酸有重叠),以确定这两个区域的部分是否可以通过分支迁移结合起来,形成一对兼容的新子区域,这两个新子区域合在一起比原来的任何一个区域单独存在时更稳定。这些子区域被添加到碱基配对区域列表中,它们将竞争形成最佳的整体结构。然后,生成一个“超结构矩阵”,其中包含每对区域之间独特的拓扑关系。我们已经表明,可以直接从这个矩阵中选择最佳结构,而无需创建和检查每一种可能的二级结构。我们将蓝藻集胞藻5S rRNA的求解结果作为我们程序功能的一个示例包含在内。

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本文引用的文献

1
Prediction of RNA secondary structure.RNA二级结构预测
Proc Natl Acad Sci U S A. 1971 Nov;68(11):2682-5. doi: 10.1073/pnas.68.11.2682.
3
7
Stability of ribonucleic acid double-stranded helices.核糖核酸双链螺旋的稳定性
J Mol Biol. 1974 Jul 15;86(4):843-53. doi: 10.1016/0022-2836(74)90357-x.
10
Method for predicting RNA secondary structure.预测RNA二级结构的方法。
Proc Natl Acad Sci U S A. 1975 Jun;72(6):2017-21. doi: 10.1073/pnas.72.6.2017.

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