New damage model for simulating radiation-induced direct damage to biomolecular systems and experimental validation...

Area of Science:

• Biophysics
• Radiation Biology
• Computational Biology

Background:

• Radiation exposure can cause direct damage to biomolecular systems, necessitating accurate predictive models.
• Existing models often require empirical data for parameter adjustment, limiting their applicability.
• Understanding radiation-induced damage is crucial for fields ranging from medicine to astrobiology.

Purpose of the Study:

• To propose and validate a novel computational model for estimating direct radiation-induced damage to biomolecular systems.
• To demonstrate the model's effectiveness using pBR322 plasmids as a test case.
• To provide a versatile and data-efficient method for predicting radiation damage in biological contexts.

Main Methods:

• Utilized coarse-grained (CG) simulation techniques to model biomolecular geometry.
• Approximated radiation damage threshold energies via CG potential calculations.
• Employed Monte Carlo track structure (MCTS) code (Geant4-DNA) to compute cumulative absorbed energy.
• Estimated direct radiation damage by comparing CG potentials and absorbed energy.

Main Results:

• The proposed model achieved an average error of approximately 14.2% in estimating radiation damage to pBR322 plasmids.
• Simulation results closely replicated experimental data, comparable to previous studies.
• The model determined parameters without relying on empirical data, unlike existing methods.

Conclusions:

• The developed model offers a novel, convenient, and effective approach for predicting radiation-induced direct damage to biomolecular systems.
• Its applicability to DNA and other biomolecules with minimal experimental data makes it valuable for diverse research.
• This method advances the prediction of radiation effects in living organisms.