Predictions and analyses of RNA nearest neighbor parameters for modified nucleotides

The most popular RNA secondary structure prediction programs utilize free energy (Delta G degrees(37)) minimization and rely upon thermodynamic parameters from the nearest neighbor (NN) model. Experimental parameters are derived from a series of optical melting experiments; however, acquiring enough melt data to derive accurate NN parameters with modified base pairs is expensive and time consuming. Given the multitude of known natural modifications and the continuing use and development of unnatural nucleotides, experimentally characterizing all modified NNs is impractical. This dilemma necessitates a computational model that can predict NN thermodynamics where experimental data is scarce or absent. Here, we present a combined molecular dynamics/quantum mechanics protocol that accurately predicts experimental NN Delta G degrees(37) parameters for modified nucleotides with neighboring Watson-Crick base pairs. NN predictions forWatsonCrick and modified base pairs yielded an overall RMSD of 0.32 kcal/mol when compared with experimentally derived parameters. NN predictions involving modified bases without experimental parameters (N-6-methyladenosine, 2-aminopurineriboside, and 5-methylcytidine) demonstrated promising agreement with available experimentalmelt data. This procedure not only yields accurate NN Delta G degrees(37) predictions but also quantifies stacking and hydrogen bonding differences between modified NNs and their canonical counterparts, allowing investigators to identify energetic differences and providing insight into sources of (de)stabilization from nucleotide modifications.