RNA Unwinding from Reweighted Pulling Simulations

Colizzi, Francesco; Bussi, Giovanni

doi:10.1021/ja210531q

Cited by 40 publications

(56 citation statements)

References 54 publications

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“…The existence of the trapped state, which was missed in previous studies (74,75), makes the overall folding process more complex. The kinetics of this elementary folding step cannot be simply described by a two-state process (i.e., the kinetics are multistate).…”

Section: Discussionmentioning

confidence: 93%

“…Previous pulling simulations suggested that a 3′-base is more stable than its 5′-base pairing partner. In a folding reaction, the 3′-base is likely to fold first through single-stranded base stacking, followed by folding of the 5′-base through base pairing with the 3′-base (75,84,95,96). Here, we focus on the second step, namely, the folding kinetics of the 5′-base (nucleotide G1) after the 3′-base (nucleotide C6) is folded into the native state (Fig.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Understanding the kinetic mechanism of RNA single base pair formation

Chen

2015

Proc. Natl. Acad. Sci. U.S.A.

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RNA functions are intrinsically tied to folding kinetics. The most elementary step in RNA folding is the closing and opening of a base pair. Understanding this elementary rate process is the basis for RNA folding kinetics studies. Previous studies mostly focused on the unfolding of base pairs. Here, based on a hybrid approach, we investigate the folding process at level of single base pairing/stacking. The study, which integrates molecular dynamics simulation, kinetic Monte Carlo simulation, and master equation methods, uncovers two alternative dominant pathways: Starting from the unfolded state, the nucleotide backbone first folds to the native conformation, followed by subsequent adjustment of the base conformation. During the base conformational rearrangement, the backbone either retains the native conformation or switches to nonnative conformations in order to lower the kinetic barrier for base rearrangement. The method enables quantification of kinetic partitioning among the different pathways. Moreover, the simulation reveals several intriguing ion binding/ dissociation signatures for the conformational changes. Our approach may be useful for developing a base pair opening/closing rate model. RNAs perform critical cellular functions at the level of gene expression and regulation (1-4). RNA functions are determined not only by RNA structure or structure motifs [e.g., tetraloop hairpins (5, 6)] but also by conformational distributions and dynamics and kinetics of conformational changes. For example, riboswitches can adopt different conformations in response to specific conditions of the cellular environment (7,8). Understanding the kinetics, such as the rate and pathways for the conformational changes, is critical for deciphering the mechanism of RNA function (9-19). Extensive experimental and theoretical studies on RNA folding kinetics have provided significant insights into the kinetic mechanism of RNA functions (19-36). However, due to the complexity of the RNA folding energy landscape (37-46) and the limitations of experimental tools (47-55), many fundamental problems, including single base flipping and base pair formation and fraying, remain unresolved. These unsolved fundamental problems have hampered our ability to resolve other important issues, such as RNA hairpin and larger structure folding kinetics. Several key questions remain unanswered, such as whether the hairpin folding is rate-limited by the conformational search of the native base pairs, whose formation leads to fast downhill folding of the whole structure, or by the breaking of misfolded base pairs before refolding to the native structure (18,19,(54)(55)(56)(57)(58)(59)(60)(61)(62)(63)(64)(65)(66)(67)(68)(69)(70)(71)(72)(73).Motivated by the need to understand the basic steps of nucleic acids folding, Hagan et al. (74) performed forty-three 200-ps unfolding trajectories at 400 K and identified both on-and offpathway intermediates and two dominant unfolding pathways for a terminal C-G base pair in a DNA duplex. In one of the pathways, bas...

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Section: Discussionmentioning

confidence: 93%

Section: Methodsmentioning

confidence: 99%

Understanding the kinetic mechanism of RNA single base pair formation

Chen

2015

Proc. Natl. Acad. Sci. U.S.A.

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“…We also stress that being able to reproduce the fluctuations of the bases is by itself an advantage because their functional role is of primary importance in nucleic acids and their dynamics can affect different aspects of the behavior of RNA molecules (see, e.g., Refs. [3,69,78]).…”

Section: Discussionmentioning

confidence: 99%

Elastic network models for RNA: a comparative assessment with molecular dynamics and SHAPE experiments

et al. 2015

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Elastic network models (ENMs) are valuable and efficient tools for characterizing the collective internal dynamics of proteins based on the knowledge of their native structures. The increasing evidence that the biological functionality of RNAs is often linked to their innate internal motions poses the question of whether ENM approaches can be successfully extended to this class of biomolecules. This issue is tackled here by considering various families of elastic networks of increasing complexity applied to a representative set of RNAs. The fluctuations predicted by the alternative ENMs are stringently validated by comparison against extensive molecular dynamics simulations and SHAPE experiments. We find that simulations and experimental data are systematically best reproduced by either an all-atom or a three-beads-per-nucleotide representation (sugar-base-phosphate), with the latter arguably providing the best balance of accuracy and computational complexity.

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“…[1][2][3][4][5][6][7][8][9] In the case of RNA folding, a few partly successful atomistic simulations have been reported. [10][11][12][13] However, recent extensive simulations of unstructured oligonucleotides for which converged sampling is affordable have unambiguously shown that current force-field parameters are not accurate enough to reproduce solution experiments.…”

Section: Introductionmentioning

confidence: 99%

Combining Simulations and Solution Experiments as a Paradigm for RNA Force Field Refinement

Cesari

Gil-Ley

Bussi

2016

J. Chem. Theory Comput.

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110

217

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Recent computational efforts have shown that the current potential energy models used in molecular dynamics are not accurate enough to describe the conformational ensemble of RNA oligomers and suggest that molecular dynamics should be complemented with experimental data. We here propose a scheme based on the maximum entropy principle to combine simulations with bulk experiments. In the proposed scheme the noise arising from both the measurements and the forward models used to back calculate the experimental observables is explicitly taken into account. The method is tested on RNA nucleosides and is then used to construct chemically consistent corrections to the Amber RNA force field that allow a large set of experimental data on nucleosides and dinucleosides to be correctly reproduced. The transferability of these corrections is assessed against independent data on tetranucleotides and displays a previously unreported agreement with experiments. This procedure can be applied to enforce multiple experimental data on multiple systems in a self-consistent framework thus suggesting a new paradigm for force field refinement.

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RNA Unwinding from Reweighted Pulling Simulations

Cited by 40 publications

References 54 publications

Understanding the kinetic mechanism of RNA single base pair formation

Understanding the kinetic mechanism of RNA single base pair formation

Elastic network models for RNA: a comparative assessment with molecular dynamics and SHAPE experiments

Combining Simulations and Solution Experiments as a Paradigm for RNA Force Field Refinement

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