Molecular renormalization group coarse-graining of polymer chains: application to double-stranded DNA

Area of Science:

• Computational Biology
• Biophysics
• Polymer Physics

Background:

• Atomistic simulations are computationally expensive for large biological systems.
• Coarse-graining simplifies models but often struggles to accurately represent complex correlations.
• Developing accurate coarse-grained models is crucial for studying DNA at longer timescales and length scales.

Purpose of the Study:

• To develop an accurate coarse-grained model for double-stranded DNA.
• To systematically derive the model from atomistic simulations using a novel renormalization approach.
• To improve the computational efficiency and accuracy of coarse-grained polymer simulations.

Main Methods:

• Systematic derivation of a coarse-grained DNA model from atomistic simulations.
• Application of molecular renormalization group (MRG) techniques.
• Matching correlators between atomistic and coarse-grained simulations.
• Utilizing a compact set of Hamiltonian basis functions based on molecular interaction potentials.

Main Results:

• Developed an accurate coarse-grained model for double-stranded DNA.
• Successfully reproduced many-body effects and polymer correlations at low computational cost.
• Achieved excellent agreement between atomistic and coarse-grained distribution functions for various structural observables.
• Demonstrated the ability to capture correlations among polymeric degrees of freedom, a long-standing challenge.

Conclusions:

• The developed MRG coarse-graining technique provides an accurate and computationally efficient method for simulating DNA.
• This approach effectively addresses the challenge of capturing complex correlations in polymer systems.
• The method shows promise for studying larger biopolymer dynamics and other complex biological problems.