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Influence of thermodynamically unfavorable secondary structures on DNA hybridization kinetics.

ABSTRACT: Nucleic acid secondary structure plays an important role in nucleic acid-nucleic acid recognition/hybridization processes, and is also a vital consideration in DNA nanotechnology. Although the influence of stable secondary structures on hybridization kinetics has been characterized, unstable secondary structures, which show positive ?G° with self-folding, can also form, and their effects have not been systematically investigated. Such thermodynamically unfavorable secondary structures should not be ignored in DNA hybridization kinetics, especially under isothermal conditions. Here, we report that positive ?G° secondary structures can change the hybridization rate by two-orders of magnitude, despite the fact that their hybridization obeyed second-order reaction kinetics. The temperature dependence of hybridization rates showed non-Arrhenius behavior; thus, their hybridization is considered to be nucleation limited. We derived a model describing how ?G° positive secondary structures affect hybridization kinetics in stopped-flow experiments with 47 pairs of oligonucleotides. The calculated hybridization rates, which were based on the model, quantitatively agreed with the experimental rate constant.

SUBMITTER: Hata H

PROVIDER: S-EPMC5778496 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Influence of thermodynamically unfavorable secondary structures on DNA hybridization kinetics.

Hata Hiroaki H Kitajima Tetsuro T Suyama Akira A

Nucleic acids research 20180101 2

Nucleic acid secondary structure plays an important role in nucleic acid-nucleic acid recognition/hybridization processes, and is also a vital consideration in DNA nanotechnology. Although the influence of stable secondary structures on hybridization kinetics has been characterized, unstable secondary structures, which show positive ΔG° with self-folding, can also form, and their effects have not been systematically investigated. Such thermodynamically unfavorable secondary structures should not ...[more]

PMID: 29220504

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Project description:BackgroundThe dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function.ResultsWe introduce a thermodynamically consistent model calibration (TCMC) method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints) into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from http://www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database.ConclusionsTCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new models. Furthermore, TCMC can provide dimensionality reduction, better estimation performance, and lower computational complexity, and can help to alleviate the problem of data overfitting.

Dataset Information

Influence of thermodynamically unfavorable secondary structures on DNA hybridization kinetics.

Publications

Influence of thermodynamically unfavorable secondary structures on DNA hybridization kinetics.

Similar Datasets

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