High-resolution reversible folding of hyperstable RNA tetraloops using molecular dynamics simulations

Abstract

We report the de novo folding of three hyperstable RNA tetraloops to 1-3 Å rmsd from their experimentally determined structures using molecular dynamics simulations initialized in the unfolded state. RNA tetraloops with loop sequences UUCG, GCAA, or CUUG are hyperstable because of the formation of noncanonical loop-stabilizing interactions, and they are all faithfully reproduced to angstrom-level accuracy in replica exchange molecular dynamics simulations, including explicit solvent and ion molecules. This accuracy is accomplished using unique RNA parameters, in which biases that favor rigid, highly stacked conformations are corrected to accurately capture the inherent flexibility of ssRNA loops, accurate base stacking energetics, and purine syn-anti interconversions. In a departure from traditional quantum chemistrycentric approaches to force field optimization, our parameters are calibrated directly from thermodynamic and kinetic measurements of intra-and internucleotide structural transitions. The ability to recapitulate the signature noncanonical interactions of the three most abundant hyperstable stem loop motifs represents a significant milestone to the accurate prediction of RNA tertiary structure using unbiased all-atom molecular dynamics simulations.RNA folding | molecular simulations S tructured RNAs exhibit a distinct preference for loops of precisely 4 nt, which was originally noted by Woese et al. (1) using comparative sequence analysis of ribosomes. Approximately 70% of these tetraloops are comprised of just three specific loop sequences: UUCG, GCAA, or CUUG. The abundance of these sequences is thermodynamic in origin, because each motif forms a unique network of noncanonical interactions within their loops that stabilizes the folded state. The abundance of high-resolution structural and thermodynamic data available for these motifs coupled with their characteristic noncanonical signatures make them ideal for adjudicating the accuracy of RNA folding simulations.RNA folding is understood to be hierarchical in nature, with secondary and tertiary folds stabilized by distinct thermodynamic driving forces (2). Secondary structure (the formation of canonical helices stabilized by Watson-Crick base pairs) can be accurately predicted from the nucleotide sequence alone using simple nearest neighbor thermodynamic models (3). In contrast, tertiary structure formation is a subtle competition between intrinsic flexibility of single-stranded segments, rigidity imparted from base-stacking interactions, stabilization of noncanonical hydrogen bonding patterns, and site-specific ion binding. In principle, a molecular dynamics simulation using a properly calibrated force field should capture all of the physicochemical properties of ribonucleotides relevant to the RNA folding process. Up until now, however, even small, fast-folding tetraloops cannot be accurately and reversibly folded from the unfolded state (4-6). In contrast, numerous documented successes have been reported using de novo protein folding with all-ato...

Free-energy landscape of a hyperstable RNA tetraloop

“…The fourth A-RNA centroid shows A 5 and A 6 mutually stacked and extended out and away from the rest of the loop. This structure has been observed in previous simulations as a transition state between the more compact loops in centroids 1 and 2 and the experimental folded state (27).…”

“…These tetraloop structures have been explored through multiple experimental (16)(17)(18)(19)(20)(21)(22)(23) and computational (24)(25)(26)(27) analyses that have revealed important clues about RNA thermodynamic stability and relate to the processes that govern the formation and stabilization of basic RNA molecules. Many tetraloops containing the conserved nucleotide sequence GNRA (N = A,C, G,U; R = A,G) possess an inherent global flexibility that manifests through multiple configurational states (19,21,22,28).…”

Multiscale simulation of DNA

“…Recalibration of stacking, if needed, should start from a careful characterization of the physical origins of any potential bias, which can be related to a bad balance of hydrophobic/hydrophilic interactions, to a poor electrostatic model for nucleosides, to incorrect van der Waals terms for nucleobases, or to the intrinsic shortcomings of a pair-wise additive spherically-shaped non-bonded potential. In any case, at least in our hands, a simple scaling of van der Waals parameters [46] This result argue the prevalent idea that DNA deformation can be described by means of nearneighbor harmonic models [40•]. An in-depth analysis of non-harmonic deformations in DNA [41,58] characterized the atomistic mechanisms of this movement, the role of ions in DNA polymorphism, and the surprising correlation between apparently disconnected degrees of freedom in the DNA.…”

“…The most important one is linked to the simplicity of the non-bonded potentials. For example, Chen and Garcia have suggested that stacking is overestimated by AMBER family of force-fields [46], an idea that has been supported by other authors [47], which compared theoretical and experimental estimates of stacking free energy of nucleobases, finding that the force-field overestimates stacking by ~1.5 kcal·mol -1 . Without arguing on the validity of the results, some caution is needed in their interpretation since: i) differences around 1 kcal·mol -1 are probably within the range of accuracy of a classical force-field; ii) experimental numbers are extremely noisy [47]; and iii)…”

Free Energy Landscape of GAGA and UUCG RNA Tetraloops

“…2 While simulations initialized in the vicinity of the native state are stable on short time-scales under a variety of simulation conditions, [3][4][5][6][7][8] more recent works strongly suggest that these systems are not correctly modeled by the current Amber force field. [9][10][11][12][13][14] Although different improvements have been proposed, 15 there is growing evidence that none of the available corrections are able to capture the crucial non-canonical interactions present in these tetraloops. 12,13 Despite their small size, an ergodic sampling of these systems requires substantial computational resources, in the order of hundreds of µs using massively parallel simulations.…”