Thermodynamic determination of RNA duplex stability in magnesium solutions

The prediction of RNA secondary structure and thermodynamics from sequence relies on free energy minimization and nearest neighbor parameters. Currently, algorithms used to make these predictions are based on parameters from optical melting studies performed in 1 M NaCl. However, many physiological and biochemical buffers containing RNA include much lower concentrations of monovalent cations and the presence of divalent cations. In order to improve these algorithms, thermodynamic data was previously collected for RNA duplexes in solutions containing 71, 121, 221, and 621 mM Na+. From this data, correction factors for free energy (Delta G(37)degrees) and melting temperature (T-m) were derived. Despite these newly derived correction factors for sodium, the stabilizing effects of magnesium have been ignored. Here, the same RNA duplexes were melted in solutions containing 0.5, 1.5, 3.0, and 10.0 mM Mg2+ in the absence of monovalent cations. Correction factors for T-m and Delta G(37)degrees were derived to scale the current parameters to a range of magnesium concentrations. The T-m correction factor predicts the melting temperature within 1.2 degrees C, and the Delta G(37)degrees correction factor predicts the free energy within 0.30 kcal/mol. These newly derived magnesium correction factors can be incorporated into algorithms that predict RNA secondary structure and stability from sequence. SIGNIFICANCE RNA secondary structure prediction guides a variety of experimental methods involving RNA. Nearest neighbor parameters derived from RNA solutions in 1 M NaCl can be used to predict RNA secondary structure; however, these conditions are far from native cellular conditions. Here, we scale melting temperature (T-m) and free energy (Delta G(37)degrees) predictive algorithms (derived from nearest neighbor parameters) to a concentration range of magnesium that is within those found in cellular environments and in many buffers designed to mimic cellular conditions. These new predictive algorithms can be used to more accurately predict RNA secondary structure from sequence in magnesium-containing solutions that mimic cell-like conditions.

Automated summary

Prediction of RNA secondary structure and thermodynamics from sequence relies on free energy minimization and nearest neighbor parameters. Algorithms used for these predictions are based on parameters from optical melting studies performed in 1 M NaCl, but physiological and biochemical buffers often contain lower concentrations of monovalent cations and the presence of divalent cations. To improve these algorithms, thermodynamic data for RNA duplexes in solutions containing different concentrations of Na+ and Mg2+ were collected and correction factors were derived. These newly derived correction factors for sodium and magnesium can be incorporated into algorithms to predict RNA secondary structure and stability from sequence.