AIMS Biophysics (May 2023)
On the dimensionless model of the transcription bubble dynamics
Abstract
The dynamics of transcription bubbles is modeled using a system of nonlinear differential equations, the one-soliton solutions of which (kinks), are interpreted as a mathematical images of transcription bubbles. These equations contain a lot of DNA dynamic parameters, including the moments of inertia of nitrous bases, distances between base pairs, distances from the centers of mass of bases to sugar-phosphate chains, rigidity of the sugar-phosphate backbone, and interactions between bases within pairs. However, estimates of the parameter values are often difficult, and it is not convenient or simple to operate with such multi-parameter systems. One of the ways to reduce the number of the DNA dynamic parameters is to transform the model equations to a dimensionless form. In this work, we construct a dimensionless DNA model and apply it to study transcription bubbles dynamics. We show that transformation to a dimensionless form really leads to a decrease in the number of the model parameters and really simplifies the analysis of model equations and their solutions.
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