Sequence-Dependent Effects in the Cyclization of Short DNA

Area of Science:

• Computational biology
• Biophysics
• Molecular modeling

Background:

• Estimating DNA ring-closure properties is crucial for understanding DNA mechanics.
• Traditional methods struggle with the complexity of short DNA chains and sequence-dependent variations.
• Accurate modeling requires accounting for base-pair step variability and conformational couplings.

Purpose of the Study:

• To develop a computationally efficient Monte Carlo approach for estimating DNA ring-closure properties.
• To investigate the influence of DNA structural features on cyclization.
• To accurately predict J factors for short DNA chains.

Main Methods:

• Developed a Gaussian sampling Monte Carlo method treating DNA as base-pair steps with sequence-dependent elastic potentials.
• Incorporated restrictions on base-pair orientation and displacement for J factor computation.
• Utilized Alexandrowicz half-chain sampling for enhanced configuration generation.

Main Results:

• The new method accurately estimates J factors for DNA chains of arbitrary length, achieving sample sizes up to O(10^14).
• Sequence-dependent features like intrinsic curvature and roll-twist coupling reconcile computed J factors with experimental data for short DNA.
• Roll-twist coupling was found to reduce oscillations in J factors versus chain length.

Conclusions:

• The developed Monte Carlo approach provides accurate and efficient estimation of DNA ring-closure properties.
• Intrinsic DNA structural features, not significant distortions, explain observed J factors in short DNA chains.
• The findings offer insights into DNA conformational dynamics and sequence-structure-function relationships.