Accurate Sequence-Dependent Coarse-Grained Model for Conformational and Elastic Properties of Double-Stranded DNA

Area of Science:

• Computational Biology
• Biophysics
• Molecular Modeling

Background:

• Understanding DNA structure and dynamics is crucial for molecular biology.
• Existing coarse-grained models often lack sequence-dependent accuracy.
• Atomistic simulations provide detailed insights but are computationally expensive.

Purpose of the Study:

• To develop a sequence-dependent coarse-grained model for double-stranded DNA (dsDNA).
• To achieve high fidelity in predicting conformational and elastic properties of dsDNA.
• To provide a computationally efficient tool for studying DNA in cellular processes.

Main Methods:

• Introduced MADna, a coarse-grained model with three beads per nucleotide (sugar, base, phosphate).
• Incorporated sequence dependence via step-dependent parametrization of bonded interactions.
• Validated model predictions against all-atom simulations and experimental data.

Main Results:

• MADna accurately captures sequence-dependent conformational and elastic features of dsDNA.
• Model predictions show excellent agreement with experimental data for moduli, couplings, persistence length, and helical pitch.
• The model's precision is comparable to atomistic simulations.

Conclusions:

• MADna offers a reliable and computationally efficient coarse-grained description of dsDNA.
• The model facilitates the rationalization of single-molecule experiments and the study of DNA in cellular contexts.
• MADna is easily integrated into standard simulation engines like LAMMPS.