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改进的模型来预测三核苷酸凸起对 RNA 双链稳定性的自由能贡献。

Improved model to predict the free energy contribution of trinucleotide bulges to RNA duplex stability.

机构信息

Department of Chemistry, Saint Louis University , Saint Louis, Missouri 63103, United States.

出版信息

Biochemistry. 2014 Jun 3;53(21):3502-8. doi: 10.1021/bi500204e. Epub 2014 May 22.

Abstract

Trinucleotide bulges in RNA commonly occur in nature. Yet, little data exists concerning the thermodynamic parameters of this motif. Algorithms that predict RNA secondary structure from sequence currently attribute a constant free energy value of 3.2 kcal/mol to all trinucleotide bulges, regardless of bulge sequence. To test the accuracy of this model, RNA duplexes that contain frequent naturally occurring trinucleotide bulges were optically melted, and their thermodynamic parameters-enthalpy, entropy, free energy, and melting temperature-were determined. The thermodynamic data were used to derive a new model to predict the free energy contribution of trinucleotide bulges to RNA duplex stability: ΔG°37, trint bulge = ΔG°37, bulge + ΔG°37, AU + ΔG°37, GU. The parameter ΔG°37, bulge is variable depending upon the purine and pyrimidine composition of the bulge, ΔG°37, AU is a 0.49 kcal/mol penalty for an A-U closing pair, and ΔG° 37, GU is a -0.56 kcal/mol bonus for a G-U closing pair. With both closing pair and bulge sequence taken into account, this new model predicts free energy values within 0.30 kcal/mol of the experimental value. The new model can be used by algorithms that predict RNA free energies as well as algorithms that use free energy minimization to predict RNA secondary structure from sequence.

摘要

RNA 中的三核苷酸凸起通常存在于自然界中。然而,关于这种模体的热力学参数的数据很少。目前,从序列预测 RNA 二级结构的算法将所有三核苷酸凸起的自由能值恒定为 3.2 kcal/mol,而不管凸起序列如何。为了测试该模型的准确性,我们对含有频繁出现的天然三核苷酸凸起的 RNA 双链体进行了光学熔融,并确定了它们的热力学参数-焓、熵、自由能和熔点。热力学数据用于推导出一个新的模型来预测三核苷酸凸起对 RNA 双链体稳定性的自由能贡献:ΔG°37,trint bulge = ΔG°37,bulge + ΔG°37, AU + ΔG°37, GU。参数 ΔG°37,bulge 取决于凸起的嘌呤和嘧啶组成,ΔG°37, AU 是 A-U 封闭对的 0.49 kcal/mol 罚分,而 ΔG°37, GU 是 G-U 封闭对的-0.56 kcal/mol 奖励。同时考虑到封闭对和凸起序列,该新模型预测的自由能值与实验值相差 0.30 kcal/mol 以内。该新模型可用于预测 RNA 自由能的算法以及使用自由能最小化从序列预测 RNA 二级结构的算法。

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