Molecular Dynamics Simulations of 2-Aminopurine-Labeled Dinucleoside Monophosphates Reveal Multiscale Stacking Kinetics

Remington, Jacob M.; McCullagh, Martin; Kohler, Bern

doi:10.1021/acs.jpcb.8b12172

Cited by 4 publications

(7 citation statements)

References 89 publications

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“…83 Recently, it has been shown that conformational transformations in RNA oligonucleotides are multi-time-scale phenomena, which occur within the range of a few nanoseconds to 80 ns. 84 It has also been argued that the heterogeneous decay of fluorescence signals in RNA DNMPs labeled with 2-aminopurine (2Ap) is an indication of the variability of stacked structures. 85 Furthermore, femtosecond spectroscopy has shown the importance of the RNA ability to adopt multiple stacked states, especially in a highly dynamic structure like a tetraloop.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

Evaluating Geometric Definitions of Stacking for RNA Dinucleoside Monophosphates Using Molecular Mechanics Calculations

Taghavi

Riveros

Wales

et al. 2022

J. Chem. Theory Comput.

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RNA modulation via small molecules is a novel approach in pharmacotherapies, where the determination of the structural properties of RNA motifs is considered a promising way to develop drugs capable of targeting RNA structures to control diseases. However, due to the complexity and dynamic nature of RNA molecules, the determination of RNA structures using experimental approaches is not always feasible, and computational models employing force fields can provide important insight. The quality of the force field will determine how well the predictions are compared to experimental observables. Stacking in nucleic acids is one such structural property, originating mainly from London dispersion forces, which are quantum mechanical and are included in molecular mechanics force fields through nonbonded interactions. Geometric descriptions are utilized to decide if two residues are stacked and hence to calculate the stacking free energies for RNA dinucleoside monophosphates (DNMPs) through statistical mechanics for comparison with experimental thermodynamics data. Here, we benchmark four different stacking definitions using molecular dynamics (MD) trajectories for 16 RNA DNMPs produced by two different force fields (RNA-IL and ff99OL3) and show that our stacking definition better correlates with the experimental thermodynamics data. While predictions within an accuracy of 0.2 kcal/mol at 300 K were observed in RNA CC, CU, UC, AG, GA, and GG, stacked states of purine−pyrimidine and pyrimidine− purine DNMPs, respectively, were typically underpredicted and overpredicted. Additionally, population distributions of RNA UU DNMPs were poorly predicted by both force fields, implying a requirement for further force field revisions. We further discuss the differences predicted by each RNA force field. Finally, we show that discrete path sampling (DPS) calculations can provide valuable information and complement the MD simulations. We propose the use of experimental thermodynamics data for RNA DNMPs as benchmarks for testing RNA force fields.

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Section: ■ Results and Discussionmentioning

confidence: 99%

Evaluating Geometric Definitions of Stacking for RNA Dinucleoside Monophosphates Using Molecular Mechanics Calculations

Taghavi

Riveros

Wales

et al. 2022

J. Chem. Theory Comput.

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“…We observe that the dynamical fingerprinting approach presents an elegant means to compare experimental relaxation data directly against a Markov state model extracted from simulation data in terms of a "fingerprint" of peaks with amplitudes and time scales related to the relaxation of particular system observables. 122 These techniques have been previously employed to in applications to base stacking of DNA dinucleoside monophosphates 123 and RNA. 92 We explored the use of this approach to validate the MD simulation data but encountered challenges in resolving fast dynamical motions below the lag time of the fitted MSM and the extremely high computational cost of collecting sufficient simulation data to fit MSMs at each temperature for which experimental data was collected.…”

Section: Introductionmentioning

confidence: 99%

Determining Sequence-Dependent DNA Oligonucleotide Hybridization and Dehybridization Mechanisms Using Coarse-Grained Molecular Simulation, Markov State Models, and Infrared Spectroscopy

et al. 2021

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A robust understanding of the sequence-dependent thermodynamics of DNA hybridization has enabled rapid advances in DNA nanotechnology. A fundamental understanding of the sequence-dependent kinetics and mechanisms of hybridization and dehybridization remains comparatively underdeveloped. In this work, we establish new understanding of the sequence-dependent hybridization/dehybridization kinetics and mechanism within a family of self-complementary pairs of 10-mer DNA oligomers by integrating coarse-grained molecular simulation, machine learning of the slow dynamical modes, data-driven inference of long-time kinetic models, and experimental temperature-jump infrared spectroscopy. For a repetitive ATATATATAT sequence, we resolve a rugged dynamical landscape comprising multiple metastable states, numerous competing hybridization/dehybridization pathways, and a spectrum of dynamical relaxations. Introduction of a G:C pair at the terminus (GATATATATC) or center (ATATGCATAT) of the sequence reduces the ruggedness of the dynamics landscape by eliminating a number of metastable states and reducing the number of competing dynamical pathways. Only by introducing a G:C pair midway between the terminus and the center to maximally disrupt the repetitive nature of the sequence (ATGATATCAT) do we recover a canonical “all-or-nothing” two-state model of hybridization/dehybridization with no intermediate metastable states. Our results establish new understanding of the dynamical richness of sequence-dependent kinetics and mechanisms of DNA hybridization/dehybridization by furnishing quantitative and predictive kinetic models of the dynamical transition network between metastable states, present a molecular basis with which to understand experimental temperature jump data, and furnish foundational design rules by which to rationally engineer the kinetics and pathways of DNA association and dissociation for DNA nanotechnology applications.

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“…The chemical modifications in the presented non-canonical bases were assigned by analog using existing bond and dihedral types. The full set of RESP-fitted charges of the nine non-canonical bases, parameterized for parmbsc1 are given in Table S5, Supplementary Materials , with literature values [ 29 , 30 , 31 , 32 , 33 , 34 ] where available. Parenthetically, an inspection of Table S5 shows the RMS deviations between our charges and those from the literature to be on the same order of magnitude, and in the same direction, as the differences between charges derived from QM-based models for the canonical residues in parm94 (c.f., Figure 1 A).…”

Section: Resultsmentioning

confidence: 99%

Self-Consistent Parameterization of DNA Residues for the Non-Polarizable AMBER Force Fields

Schneider

Albrecht

Huang

et al. 2022

Life

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Fixed-charge (non-polarizable) forcefields are accurate and computationally efficient tools for modeling the molecular dynamics of nucleic acid polymers, particularly DNA, well into the µs timescale. The continued utility of these forcefields depends in part on expanding the residue set in step with advancing nucleic acid chemistry and biology. A key step in parameterizing new residues is charge derivation which is self-consistent with the existing residues. As atomic charges are derived by fitting against molecular electrostatic potentials, appropriate structural models are critical. Benchmarking against the existing charge set used in current AMBER nucleic acid forcefields, we report that quantum mechanical models of deoxynucleosides, even at a high level of theory, are not optimal structures for charge derivation. Instead, structures from molecular mechanics minimization yield charges with up to 6-fold lower RMS deviation from the published values, due to the choice of such an approach in the derivation of the original charge set. We present a contemporary protocol for rendering self-consistent charges as well as optimized charges for a panel of nine non-canonical residues that will permit comparison with literature as well as studying the dynamics of novel DNA polymers.

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Molecular Dynamics Simulations of 2-Aminopurine-Labeled Dinucleoside Monophosphates Reveal Multiscale Stacking Kinetics

Cited by 4 publications

References 89 publications

Evaluating Geometric Definitions of Stacking for RNA Dinucleoside Monophosphates Using Molecular Mechanics Calculations

Evaluating Geometric Definitions of Stacking for RNA Dinucleoside Monophosphates Using Molecular Mechanics Calculations

Determining Sequence-Dependent DNA Oligonucleotide Hybridization and Dehybridization Mechanisms Using Coarse-Grained Molecular Simulation, Markov State Models, and Infrared Spectroscopy

Self-Consistent Parameterization of DNA Residues for the Non-Polarizable AMBER Force Fields

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