A polymer physics model of the interphase cell nucleus for radiobiological simulations
Man Zhao1, Guomin Huang2, Zi Xu1
1National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, 518116, People's Republic of China.
Scientific Reports
|February 9, 2026
Summary
This study models 3D chromatin architecture using polymer physics to predict DNA damage and chromosome aberrations. The new model accurately simulates radiation effects, improving radiobiology predictions.
Area of Science:
- Computational Biology
- Structural Biology
- Radiobiology
Background:
- Advanced imaging and chromosome conformation capture (Hi-C) provide insights into chromatin structure.
- Integrating these insights into radiobiology modeling remains a challenge.
- Existing models struggle with computational costs and accuracy.
Purpose of the Study:
- To develop a polymer physics-based model for simulating 3D chromatin architecture and chromosome aberrations.
- To benchmark the model against experimental radiobiology data.
- To bridge structural biology and radiobiological simulations for improved DNA damage prediction.
Main Methods:
- Utilized polymer physics principles to describe chromosomal and chromatin interactions.
- Employed a multi-stage relaxation strategy to manage computational cost.
- Implemented a distance-dependent DNA end rejoining model and graph theory for aberration simulation.
Main Results:
- Successfully reproduced 3D chromatin architectures (territories, subcompartments, domains, loops).
- Predicted contact maps and probabilities consistent with Hi-C measurements.
- Model predictions for dicentrics, deletions, and total aberrations aligned within 20% of experimental data for gamma rays and alpha particles.
Conclusions:
- The polymer physics model accurately simulates chromatin organization and radiation-induced chromosome aberrations.
- The model shows significant improvement over previous methods, aligning experimental and simulation data.
- This approach holds strong potential for predicting DNA damage and enhancing radiobiological simulations, especially for high-LET radiation effects.
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