Tomcho Jeremy C, Tillman Magdalena R, Znosko Brent M
Department of Chemistry, Saint Louis University , Saint Louis, Missouri 63103, United States.
Biochemistry. 2015 Sep 1;54(34):5290-6. doi: 10.1021/acs.biochem.5b00474. Epub 2015 Aug 19.
Predicting the secondary structure of RNA is an intermediate in predicting RNA three-dimensional structure. Commonly, determining RNA secondary structure from sequence uses free energy minimization and nearest neighbor parameters. Current algorithms utilize a sequence-independent model to predict free energy contributions of dinucleotide bulges. To determine if a sequence-dependent model would be more accurate, short RNA duplexes containing dinucleotide bulges with different sequences and nearest neighbor combinations were optically melted to derive thermodynamic parameters. These data suggested energy contributions of dinucleotide bulges were sequence-dependent, and a sequence-dependent model was derived. This model assigns free energy penalties based on the identity of nucleotides in the bulge (3.06 kcal/mol for two purines, 2.93 kcal/mol for two pyrimidines, 2.71 kcal/mol for 5'-purine-pyrimidine-3', and 2.41 kcal/mol for 5'-pyrimidine-purine-3'). The predictive model also includes a 0.45 kcal/mol penalty for an A-U pair adjacent to the bulge and a -0.28 kcal/mol bonus for a G-U pair adjacent to the bulge. The new sequence-dependent model results in predicted values within, on average, 0.17 kcal/mol of experimental values, a significant improvement over the sequence-independent model. This model and new experimental values can be incorporated into algorithms that predict RNA stability and secondary structure from sequence.
预测RNA的二级结构是预测RNA三维结构的一个中间环节。通常,从序列确定RNA二级结构采用自由能最小化和最近邻参数。当前的算法利用与序列无关的模型来预测二核苷酸凸起的自由能贡献。为了确定与序列相关的模型是否会更准确,对含有不同序列和最近邻组合的二核苷酸凸起的短RNA双链体进行光学熔解,以得出热力学参数。这些数据表明二核苷酸凸起的能量贡献是与序列相关的,并由此推导了一个与序列相关的模型。该模型根据凸起中核苷酸的种类来赋予自由能罚分(两个嘌呤为3.06千卡/摩尔,两个嘧啶为2.93千卡/摩尔,5'-嘌呤-嘧啶-3'为2.71千卡/摩尔,5'-嘧啶-嘌呤-3'为2.41千卡/摩尔)。该预测模型还包括对与凸起相邻的A-U碱基对有0.45千卡/摩尔的罚分,对与凸起相邻的G-U碱基对有-0.28千卡/摩尔的奖励。新的与序列相关的模型得出的预测值平均比实验值低0.17千卡/摩尔,比与序列无关的模型有显著改进。该模型和新的实验值可以纳入从序列预测RNA稳定性和二级结构的算法中。