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Two- and Three-Dimensional Modeling of RNA Structure with NMR and Thermodynamics Methods.

机译:使用NMR和热力学方法对RNA结构进行二维和三维建模。

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摘要

RNA is a biopolymer that performs a variety of functions, such as storing genetic information, splicing, protein synthesis, chemical modification of other RNAs, and silencing gene expression. These functions were demonstrated to be affected by the structure of RNA. RNA folds in a hierarchical and sequential manner, first from sequence to secondary structure. This causes it to be suitable to prediction of secondary structure by computational algorithms. In this work, improvements to the accuracy of prediction of RNA secondary structure were achieved with an updated INN-HB model. NMR constraints that may assist with secondary structure prediction were identified. Separately, the 3D structure of an RNA hairpin from influenza A was determined.;Elucidation of secondary structure can facilitate accurate prediction of tertiary structure from local or long range interactions among elements of secondary structure. The INN-HB model provides a fast approach to folding secondary structure from sequence. The database of sequences from which the GU pair INN-HB model is derived was expanded and fitted to 11 parameters. An improvement in the accuracy of the model was demonstrated with statistical tests. For AU and GU pairs, two- and three-dimensional dependencies among chemical shifts of certain protons on the orientation of the base pairs in three base pair stacks were identified. These dependencies can be applied as constraints to a free energy minimization algorithm to improve the accuracy of secondary structure prediction. The 3D structure of a 39-nt construct of a hairpin with a 3? splice in a 2 x 2 internal loop from influenza A segment 7 mRNA was determined with NMR and restrained molecular dynamics. The hairpin loop consists of a GAAA stack enclosed by an unprotonated AC pair. The internal loop is structurally dynamic. The adenosine bulge forms a base triple with a canonical GC pair. The updated GU INN-HB model predicts a favorable DeltaG°37 for the secondary structure of this hairpin.
机译:RNA是一种生物聚合物,具有多种功能,例如存储遗传信息,剪接,蛋白质合成,其他RNA的化学修饰和沉默基因表达。已证明这些功能受RNA结构的影响。 RNA以分层和顺序的方式折叠,首先是从序列到二级结构。这使得它适合通过计算算法预测二级结构。在这项工作中,使用更新的INN-HB模型提高了RNA二级结构的预测准确性。确定了可能有助于二级结构预测的NMR约束。分别地,确定了来自甲型流感的RNA发夹的3D结构。二级结构的阐明可以根据二级结构的元素之间的局部或远距离相互作用来促进三级结构的准确预测。 INN-HB模型提供了一种从序列中折叠二级结构的快速方法。扩展了生成GU对INN-HB模型的序列的数据库,并将其拟合为11个参数。统计测试证明了模型准确性的提高。对于AU和GU对,确定了某些质子化学位移对三个碱基对堆中碱基对方向的二维和三维依赖性。这些依赖性可以作为自由能最小化算法的约束条件来提高二级结构预测的准确性。具有3′的发夹的39-nt构建体的3D结构。通过NMR和受限制的分子动力学确定了来自流感A段7 mRNA的2 x 2内部环中的剪接。发夹环由一个由无质子化的AC对包围的GAAA堆栈组成。内部循环在结构上是动态的。腺苷凸起与标准GC对形成一个碱基三元组。更新的GU INN-HB模型预测该发夹的二级结构具有有利的DeltaG°37。

著录项

  • 作者

    Chen, Jonathan L.;

  • 作者单位

    University of Rochester.;

  • 授予单位 University of Rochester.;
  • 学科 Biochemistry.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 278 p.
  • 总页数 278
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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