Investigation into the mechanism and dynamics of DNA association and dissociation utilizing kinetic Monte Carlo simulations.

In this work, we present a kinetic Markov state Monte Carlo model designed to complement temperature-jump (T-jump) infrared spectroscopy experiments probing the kinetics and dynamics of short DNA oligonucleotides. The model is designed to be accessible to experimental researchers in terms of both computational simplicity and expense while providing detailed insights beyond those provided by experimental methods. The model is an extension of a thermodynamic lattice model for DNA hybridization utilizing the formalism of the nucleation-zipper mechanism. Association and dissociation trajectories were generated utilizing the Gillespie algorithm and parameters determined via fitting the association and dissociation timescales to previously published experimental data. Terminal end fraying, experimentally observed following a rapid T-jump, in the sequence 5'-ATATGCATAT-3' was replicated by the model that also demonstrated that experimentally observed fast dynamics in the sequences 5'-C(AT)nG-3', where n = 2-6, were also due to terminal end fraying. The dominant association pathways, isolated by transition pathway theory, showed two primary motifs: initiating at or next to a G:C base pair, which is enthalpically favorable and related to the increased strength of G:C base pairs, and initiating in the center of the sequence, which is entropically favorable and related to minimizing the penalty associated with the decrease in configurational entropy due to hybridization.

Length-Dependent Melting Kinetics of Short DNA Oligonucleotides Using Temperature-Jump IR Spectroscopy.

In this work, we utilize Fourier transform infrared and temperature-jump (T-jump) infrared (IR) spectroscopy to investigate the melting thermodynamics and kinetics of a series of five DNA sequences ranging from 6 to 14 base pairs long. IR spectroscopy is well suited for the study of DNA because of its ability to distinguish base-specific information, and the nanosecond time resolution of the T-jump apparatus can access the relevant range of kinetics. Eyring analysis of a two-state model examines both the activation enthalpy and entropy, providing new insights into the energetic driving forces and physical processes behind the association and dissociation while also helping to clarify the commonly observed negative activation energy. Global analysis of the thermodynamic and kinetic data applying a linear dependence of activation barriers on oligo length provides a holistic result by producing reasonable agreement between our data and existing nearest-neighbor (NN) thermodynamic parameters blending the experimental results with established predictive models. By studying the trends in the thermodynamics and kinetics as a function of length, this work demonstrates a direct correlation between the effects additional dinucleotides have on the kinetics and the NN parameters for those dinucleotides. This result further supports the development of a kinetic analogue to the thermodynamic NN parameters.

l-Proline and RNA Duplex m-Value Temperature Dependence.

The temperature dependence of l-proline interactions with the RNA dodecamer duplex surface exposed after unfolding was quantified using thermal and isothermal titration denaturation monitored by uv-absorbance. The m-value quantifying proline interactions with the RNA duplex surface area exposed after unfolding was measured using RNA duplexes with GC content ranging between 17 and 83%. The m-values from thermal denaturation decreased with increasing GC content signifying increasingly favorable proline interactions with the exposed RNA surface area. However, m-values from isothermal titration denaturation at 25.0 °C were independent of GC content and less negative than those from thermal denaturation. The m-value from isothermal titration denaturation for a 50% GC RNA duplex decreased (became more negative) as the temperature increased and was in nearly exact agreement with the m-value from thermal denaturation. Since RNA duplex transition temperatures increased with GC content, the more favorable proline interactions with the high GC content duplex surface area observed from thermal denaturation resulted from the temperature dependence of proline interactions rather than the RNA surface chemical composition. The enthalpy contribution to the m-value was positive and small (indicating a slight increase in duplex unfolding enthalpy with proline) while the entropic contribution to the m-value was positive and increased with temperature. Our results will facilitate proline's use as a probe of solvent accessible surface area changes during biochemical reactions at different reaction temperatures.

Quantifying the temperature dependence of glycine-betaine RNA duplex destabilization.

Glycine-betaine (GB) stabilizes folded protein structure because of its unfavorable thermodynamic interactions with amide oxygen and aliphatic carbon surface area exposed during protein unfolding. However, GB can attenuate nucleic acid secondary structure stability, although its mechanism of destabilization is not currently understood. Here we quantify GB interactions with the surface area exposed during thermal denaturation of nine RNA dodecamer duplexes with guanine-cytosine (GC) contents of 17-100%. Hyperchromicity values indicate increasing GB molality attenuates stacking. GB destabilizes higher-GC-content RNA duplexes to a greater extent than it does low-GC-content duplexes due to greater accumulation at the surface area exposed during unfolding. The accumulation is very sensitive to temperature and displays characteristic entropy-enthalpy compensation. Since the entropic contribution to the m-value (used to quantify GB interaction with the RNA solvent-accessible surface area exposed during denaturation) is more dependent on temperature than is the enthalpic contribution, higher-GC-content duplexes with their larger transition temperatures are destabilized to a greater extent than low-GC-content duplexes. The concentration of GB at the RNA surface area exposed during unfolding relative to bulk was quantified using the solute-partitioning model. Temperature correction predicts a GB concentration at 25 °C to be nearly independent of GC content, indicating that GB destabilizes all sequences equally at this temperature.