A sequence-dependent rigid-base model of DNA.

Area of Science:

• Computational Biology
• Biophysics
• Molecular Modeling

Background:

• Understanding DNA structure-property relationships is crucial for molecular biology.
• Sequence-dependent interactions significantly influence DNA oligomer behavior in solution.
• Existing models often lack the resolution to capture complex sequence-specific effects.

Purpose of the Study:

• To develop a hierarchy of coarse-grain, sequence-dependent models for B-form DNA.
• To investigate the phenomenon of frustration in DNA oligomers.
• To predict DNA oligomer configurations and response to sequence changes.

Main Methods:

• Introduced a hierarchy of rigid-base DNA models with varying energetic couplings and sequence dependence.
• Focused on a nearest-neighbor interaction model with dimer sequence dependence.
• Estimated model parameters using data from all-atom molecular dynamics (MD) simulations.
• Utilized Kullback-Leibler divergence for model assessment and comparison.

Main Results:

• The developed model exhibits DNA frustration, where bases cannot simultaneously minimize all interactions.
• The model accurately predicts sequence-dependent effects within and between DNA oligomers.
• It successfully predicts nonlocal structural changes resulting from local sequence variations, including point mutations.

Conclusions:

• Coarse-grain, sequence-dependent models, incorporating frustration, can effectively approximate DNA oligomer behavior in solution.
• Nearest-neighbor interactions and dimer sequence dependence are critical for capturing sequence effects.
• The model demonstrates predictive power comparable to all-atom simulations for certain properties.