Revision of AMBER Torsional Parameters for RNA Improves Free Energy Predictions for Tetramer Duplexes with GC and iGiC Base Pairs.

All-atom force fields are important for predicting thermodynamic, structural, and dynamic properties of RNA. In this paper, results are reported for thermodynamic integration calculations of free energy differences of duplex formation when CG pairs in the RNA duplexes r(CCGG)(2), r(GGCC)(2), r(GCGC)(2), and r(CGCG)(2) are replaced by isocytidine-isoguanosine (iCiG) pairs. Agreement with experiment was improved when ε/ζ, α/γ, ß, and χ torsional parameters in the AMBER99 force field were revised on the basis of quantum mechanical calculations. The revised force field, AMBER99TOR, brings free energy difference predictions to within 1.3, 1.4, 2.3, and 2.6 kcal/mol at 300 K, respectively, compared to experimental results for the thermodynamic cycles of CCGG → iCiCiGiG, GGCC → iGiGiCiC, GCGC → iGiCiGiC, and CGCG → iCiGiCiG. In contrast, unmodified AMBER99 predictions for GGCC → iGiGiCiC and GCGC → iGiCiGiC differ from experiment by 11.7 and 12.6 kcal/mol, respectively. In order to test the dynamic stability of the above duplexes with AMBER99TOR, four individual 50 ns molecular dynamics (MD) simulations in explicit solvent were run. All except r(CCGG)(2) retained A-form conformation for ≥82% of the time. This is consistent with NMR spectra of r(iGiGiCiC)(2), which reveal an A-form conformation. In MD simulations, r(CCGG)(2) retained A-form conformation 52% of the time, suggesting that its terminal base pairs may fray. The results indicate that revised backbone parameters improve predictions of RNA properties and that comparisons to measured sequence dependent thermodynamics provide useful benchmarks for testing force fields and computational methods.

NMR-assisted prediction of RNA secondary structure: identification of a probable pseudoknot in the coding region of an R2 retrotransposon.

As the rate of functional RNA sequence discovery escalates, high-throughput techniques for reliable structural determination are becoming crucial for revealing the essential features of these RNAs in a timely fashion. Computational predictions of RNA secondary structure quickly generate reasonable models but suffer from several approximations, including overly simplified models and incomplete knowledge of significant interactions. Similar problems limit the accuracy of predictions for other self-folding polymers, including DNA and peptide nucleic acid (PNA). The work presented here demonstrates that incorporating unassigned data from simple nuclear magnetic resonance (NMR) experiments into a dynamic folding algorithm greatly reduces the potential folding space of a given RNA and therefore increases the confidence and accuracy of modeling. This procedure has been packaged into an NMR-assisted prediction of secondary structure (NAPSS) algorithm that can produce pseudoknotted as well as non-pseudoknotted secondary structures. The method reveals a probable pseudoknot in the part of the coding region of the R2 retrotransposon from Bombyx mori that orchestrates second-strand DNA cleavage during insertion into the genome.