Statistical mechanics of sequence-dependent circular DNA and its application for DNA cyclization

Area of Science:

• Biophysics
• Structural Biology
• Computational Biology

Background:

• DNA cyclization is a powerful method for quantifying sequence-dependent DNA bending and flexibility.
• Existing models often assume DNA homogeneity, limiting their applicability to complex DNA structures.

Purpose of the Study:

• To extend statistical mechanics models of DNA cyclization to account for base-pair discreteness and DNA inhomogeneity.
• To develop a computationally efficient theoretical framework for analyzing DNA cyclization experiments.

Main Methods:

• Developed a statistical mechanics model incorporating discrete base pairs for inhomogeneous DNA circles.
• Analyzed equilibrium configurations and thermodynamic quantities (J factor) using harmonic approximation.
• Evaluated the effects of DNA curvature, helical repeat, and flexibility on cyclization.

Main Results:

• The model accurately predicts J factors for both homogeneous and inhomogeneous DNA.
• Demonstrated that DNA cyclization can detect minute changes in curvature (as low as 1 degree) and flexibility (a few percent).
• Achieved high consistency with Monte Carlo simulations but with significantly improved computational efficiency.

Conclusions:

• The enhanced statistical mechanics model provides a robust and efficient tool for analyzing sequence-dependent DNA bending and flexibility.
• This approach advances the systematic quantitation of DNA structural dynamics through cyclization assays.
• The model's accuracy in simulating experimental results validates its utility in biophysical research.