<p>Nonlinear molecular excitations in DNA have traditionally been studied within the framework of the nonlinear Schrödinger equation (NLSE). An alternative approach is based on the plane-base rotator model and <i>SU</i>(2)/<i>U</i>(1) generalized spin coherent states, which leads to a cubic-quintic NLSE. Higher-order nonlinearities are particularly useful for modelling complex interactions, such as those in DNA-protein systems, where multiple competing forces play a significant role. Additionally, the surrounding viscous medium introduces dissipative forces that influence the propagation of molecular excitations, resulting in energy dissipation and damping effects. These damping effects are modelled using the quasi-stationary method, which describes the system’s near-equilibrium behaviour. In this work, we analyse the evolution of nonlinear molecular excitations in DNA-protein systems, accounting for damping effects, and discuss potential applications to the transcription process.</p>

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Quasi-stationary Evolution of Cubic-quintic NLSE Drop-like Solitons in DNA-protein Systems

  • O. Pavón-Torres,
  • J. R. Collantes-Collantes,
  • M. A. Agüero-Granados

摘要

Nonlinear molecular excitations in DNA have traditionally been studied within the framework of the nonlinear Schrödinger equation (NLSE). An alternative approach is based on the plane-base rotator model and SU(2)/U(1) generalized spin coherent states, which leads to a cubic-quintic NLSE. Higher-order nonlinearities are particularly useful for modelling complex interactions, such as those in DNA-protein systems, where multiple competing forces play a significant role. Additionally, the surrounding viscous medium introduces dissipative forces that influence the propagation of molecular excitations, resulting in energy dissipation and damping effects. These damping effects are modelled using the quasi-stationary method, which describes the system’s near-equilibrium behaviour. In this work, we analyse the evolution of nonlinear molecular excitations in DNA-protein systems, accounting for damping effects, and discuss potential applications to the transcription process.