Christiansen Martha E, Znosko Brent M
Department of Chemistry, Saint Louis University, Saint Louis, Missouri 63103, USA.
Biochemistry. 2008 Apr 8;47(14):4329-36. doi: 10.1021/bi7020876. Epub 2008 Mar 11.
Because of the availability of an abundance of RNA sequence information, the ability to rapidly and accurately predict the secondary structure of RNA from sequence is becoming increasingly important. A common method for predicting RNA secondary structure from sequence is free energy minimization. Therefore, accurate free energy contributions for every RNA secondary structure motif are necessary for accurate secondary structure predictions. Tandem mismatches are prevalent in naturally occurring sequences and are biologically important. A common method for predicting the stability of a sequence asymmetric tandem mismatch relies on the stabilities of the two corresponding sequence symmetric tandem mismatches [Mathews, D. H., Sabina, J., Zuker, M., and Turner, D. H. (1999) J. Mol. Biol. 288, 911-940]. To improve the prediction of sequence asymmetric tandem mismatches, the experimental thermodynamic parameters for the 22 previously unmeasured sequence symmetric tandem mismatches are reported. These new data, however, do not improve prediction of the free energy contributions of sequence asymmetric tandem mismatches. Therefore, a new model, independent of sequence symmetric tandem mismatch free energies, is proposed. This model consists of two penalties to account for destabilizing tandem mismatches, two bonuses to account for stabilizing tandem mismatches, and two penalties to account for A-U and G-U adjacent base pairs. This model improves the prediction of asymmetric tandem mismatch free energy contributions and is likely to improve the prediction of RNA secondary structure from sequence.
由于存在大量的RNA序列信息,从序列快速准确地预测RNA二级结构的能力变得越来越重要。从序列预测RNA二级结构的常用方法是自由能最小化。因此,准确预测二级结构需要知道每个RNA二级结构基序的精确自由能贡献。串联错配在天然序列中普遍存在且具有生物学重要性。预测序列不对称串联错配稳定性的常用方法依赖于两个相应的序列对称串联错配的稳定性[马修斯,D.H.,萨比娜,J.,祖克,M.,和特纳,D.H.(1999年)《分子生物学杂志》288卷,911 - 940页]。为了改进对序列不对称串联错配的预测,本文报道了22个先前未测量的序列对称串联错配的实验热力学参数。然而,这些新数据并未改善对序列不对称串联错配自由能贡献的预测。因此,提出了一个独立于序列对称串联错配自由能的新模型。该模型包含两个用于解释串联错配去稳定化的惩罚项、两个用于解释串联错配稳定化的奖励项,以及两个用于解释A - U和G - U相邻碱基对的惩罚项。该模型改进了对不对称串联错配自由能贡献的预测,并且可能会改进从序列预测RNA二级结构的能力。