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Coarse-grained modeling of hydrodynamic behavior in DNA synthesis monomers
Xiaoping Li1, Shuang Liu2, Liwen Li2
1State Key Laboratory of Precision Measurement Technology and Instruments, Tianjin University, Tianjin, China.
The Journal of Chemical Physics
|May 22, 2026
Summary
We developed a coarse-grained model for nucleotide monomers, revealing that diffusion slows with concentration and varies by base. This impacts DNA synthesis and data storage efficiency.
Area of Science:
- * Biophysics
- * Computational Chemistry
- * Molecular Dynamics
Background:
- * Efficient DNA synthesis is vital for DNA data storage and synthetic biology.
- * Understanding nucleotide monomer diffusion in solution is key but not fully elucidated.
- * Current computational models lack the necessary scale for these dynamics.
Purpose of the Study:
- * To develop a computationally efficient model for nucleotide monomers.
- * To investigate the micro-scale dynamics of nucleotide diffusion in solution.
- * To provide insights into optimizing DNA synthesis and data storage.
Main Methods:
- * Developed a novel four-bead coarse-grained (CG) model for dimethoxytrityl (DMT)-protected nucleotide monomers.
- * Validated the CG model using Boltzmann inversion.
- * Employed the stochastic Eulerian Lagrangian method for fluid-solid interactions in simulations.
- * Conducted simulations in acetonitrile.
Main Results:
- * The CG model achieved over 20x computational efficiency compared to all-atom models.
- * Monomer diffusion decreased significantly with increasing concentration due to intermolecular interactions.
- * Channel walls imposed substantial, concentration-dependent diffusion restrictions.
- * Adenine and thymine monomers diffused slower than cytosine and guanine monomers.
Conclusions:
- * The CG model enables large-scale simulations of nucleotide dynamics.
- * Monomer diffusion is heavily influenced by concentration and confinement.
- * Base-specific diffusion rates offer a kinetic explanation for mass transfer variations in DNA synthesis.
- * Findings can inform optimization of DNA synthesis and data storage technologies.
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