Free Energy Landscape of GAGA and UUCG RNA Tetraloops

Mapping the Universe of RNA Tetraloop Folds

We report a map of RNA tetraloop conformations constructed by calculating pairwise distances among all experimentally determined four-nucleotide hairpin loops. Tetraloops with similar structures are clustered together and, as expected, the two largest clusters are the canonical GNRA and UNCG folds. We identify clusters corresponding to known tetraloop folds such as GGUG, RNYA, AGNN, and CUUG. These clusters are represented in a simple two-dimensional projection that recapitulates the relationship among the different folds. The cluster analysis also identifies 20 novel tetraloop folds that are peculiar to specific positions in ribosomal RNAs and that are stabilized by tertiary interactions. In our RNA tetraloop database we find a significant number of non-GNRA and non-UNCG sequences adopting the canonical GNRA and UNCG folds. Conversely, we find a significant number of GNRA and UNCG sequences adopting non-GNRA and non-UNCG folds. Our analysis demonstrates that there is not a simple one-to-one, but rather a many-to-many mapping between tetraloop sequence and tetraloop fold.

Improving Computational Predictions of Single-Stranded RNA Tetramers with Revised α/γ Torsional Parameters for the Amber Force Field

With current advancements in RNA based therapeutics, it is becoming crucial to utilize theoretical and computational methods to describe properly the physical properties of RNA molecules. NMR and X-ray crystallography are two powerful techniques for investigating structural properties. However, if the RNA molecules are complex or dynamic, these methods might not be adequate. For computational approaches, the quality of the force field will determine accuracy of our predictions. In this contribution, we revise the α/γ torsional parameters of RNA for amber force field using a model system representing an RNA dimer backbone. Combined with revised χ torsional parameters, previously shown to improve computational predictions, we benchmarked the revised force field on five single-stranded RNA (ssRNA) tetramers, three RNA dodecamer duplexes, and an RNA hairpin. A total of 60 μs of molecular dynamics (MD) simulations were run. We also employ the discrete path sampling (DPS) approach to compare the predictions for the revised amber force field with those for amber10. Our results indicate that the unphysical states observed with amber10 in ssRNA MD simulations are suppressed for the revised amber force field. In line with NMR experimental observations, incorporation of the revised α/γ and χ torsional parameters leads to A-form-like conformational states as the most favorable ssRNA tetramer conformations. Furthermore, the revised force field maintains the A-form geometry in regular RNA duplexes. Our revised amber force field for RNA should therefore improve structural and thermodynamic predictions for challenging RNA systems.

Noncanonical α/γ Backbone Conformations in RNA and the Accuracy of Their Description by the AMBER Force Field

The sugar-phosphate backbone of RNA can exist in diverse rotameric substates, giving RNA molecules enormous conformational variability. The most frequent noncanonical backbone conformation in RNA is α/γ = t/t, which is derived from the canonical backbone by a crankshaft motion and largely preserves the standard geometry of the RNA duplex. A similar conformation also exists in DNA, where it has been extensively studied and shown to be involved in DNA-protein interactions. However, the function of the α/γ = t/t conformation in RNA is poorly understood. Here, we present molecular dynamics simulations of several prototypical RNA structures obtained from X-ray and NMR experiments, including canonical and mismatched RNA duplexes, UUCG and GAGA tetraloops, Loop E, the sarcin-ricin loop, a parallel guanine quadruplex, and a viral pseudoknot. The stability of various noncanonical α/γ backbone conformations was analyzed with two AMBER force fields, ff99bsc0χ_OL3 and ff99bsc0χ_OL3 with the recent εζ_OL1 and β_OL1 corrections for DNA. Although some α/γ substates were stable with seemingly well-described equilibria, many were unstable in our simulations. Notably, the most frequent noncanonical conformer α/γ = t/t was unstable in both tested force fields. Possible reasons for this instability are discussed. Our work reveals a potentially important artifact in RNA force fields and highlights a need for further force field refinement.

Revised RNA Dihedral Parameters for the Amber Force Field Improve RNA Molecular Dynamics

The backbone dihedral parameters of the Amber RNA force field were improved by fitting using multiple linear regression to potential energies determined by quantum chemistry calculations. Five backbone and four glycosidic dihedral parameters were fit simultaneously to reproduce the potential energies determined by a high-level density functional theory calculation (B97D3 functional with the AUG-CC-PVTZ basis set). Umbrella sampling was used to determine conformational free energies along the dihedral angles, and these better agree with the population of conformations observed in the protein data bank for the new parameters than for the conventional parameters. Molecular dynamics simulations performed on a set of hairpin loops, duplexes and tetramers with the new parameter set show improved modeling for the structures of tetramers CCCC, CAAU, and GACC, and an RNA internal loop of noncanonical pairs, as compared to the conventional parameters. For the tetramers, the new parameters largely avoid the incorrect intercalated structures that dominate the conformational samples from the conventional parameters. For the internal loop, the major conformation solved by NMR is stable with the new parameters, but not with the conventional parameters. The new force field performs similarly to the conventional parameters for the UUCG and GCAA hairpin loops and the [U(UA)6A]2 duplex.

Predicting the Kinetics of RNA Oligonucleotides Using Markov State Models

Nowadays different experimental techniques, such as single molecule or relaxation experiments, can provide dynamic properties of biomolecular systems, but the amount of detail obtainable with these methods is often limited in terms of time or spatial resolution. Here we use state-of-the-art computational techniques, namely, atomistic molecular dynamics and Markov state models, to provide insight into the rapid dynamics of short RNA oligonucleotides, to elucidate the kinetics of stacking interactions. Analysis of multiple microsecond-long simulations indicates that the main relaxation modes of such molecules can consist of transitions between alternative folded states, rather than between random coils and native structures. After properly removing structures that are artificially stabilized by known inaccuracies of the current RNA AMBER force field, the kinetic properties predicted are consistent with the time scales of previously reported relaxation experiments.