Improved Model for Predicting the Free Energy Contribution of Dinucleotide Bulges to RNA Duplex Stability

Abstract

Predicting secondary structure of RNA is an intermediate in predicting RNA 3D 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. This 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.

A sensitivity analysis of RNA folding nearest neighbor parameters identifies a subset of free energy parameters with the greatest impact on RNA secondary structure prediction

“…Interestingly, some of these categories have already been addressed by additional experiments performed after the parameters were last assembled in 2004. For example, bulge loops and GU pairs have been studied with additional optical melting experiments ( 33 , 36 – 39 ). The results here show the importance of integrating the new data into the complete set of nearest neighbor parameters in current use.…”

Modeling Structure, Stability, and Flexibility of Double-Stranded RNAs in Salt Solutions

“…b B stands for dsRNA with bulge loop, and I stands for dsRNA with internal loop. c The experimental data are from(74)(75)(76)(77)(78)(79)(80).dsRNA Structure, Stability & Flexibility Biophysical Journal 115, 1403-1416, October 16, 2018 1411…”

Modeling structure, stability and flexibility of double-stranded RNAs in salt solutions

“…Beyond the dsRNAs with complementary sequences shown above, the stability of other 8 dsRNAs with bulge/internal loops was examined by the present model. As shown in Table 3, for the dsRNAs with single/double bulge loops of different loop lengths (sequences 1-6) and the dsRNAs with internal loops (sequences 7 and 8), the mean deviation between the predicted T m ’s and the experimental data (74-80) is ~2.6°C, which indicates that the present model with the coaxial stacking potential can roughly estimate the stability of dsRNAs with bulge/internal loops. However, such predictions especially for dsRNAs with long bulge/internal loops are not as precise as those for dsRNAs without loops.…”