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. 2022 Jun 6;23(11):6343.
doi: 10.3390/ijms23116343.

Nanoscale Calculation of Proton-Induced DNA Damage Using a Chromatin Geometry Model with Geant4-DNA

Kun Zhu  1 , Chun Wu  2 , Xiaoyu Peng  1 , Xuantao Ji  1 , Siyuan Luo  1 , Yuchen Liu  1 , Xiaodong Wang  1
Affiliations

Nanoscale Calculation of Proton-Induced DNA Damage Using a Chromatin Geometry Model with Geant4-DNA

Kun Zhu et al. Int J Mol Sci. .

Abstract

Monte Carlo simulations can quantify various types of DNA damage to evaluate the biological effects of ionizing radiation at the nanometer scale. This work presents a study simulating the DNA target response after proton irradiation. A chromatin fiber model and new physics constructors with the ELastic Scattering of Electrons and Positrons by neutral Atoms (ELSEPA) model were used to describe the DNA geometry and the physical stage of water radiolysis with the Geant4-DNA toolkit, respectively. Three key parameters (the energy threshold model for strand breaks, the physics model and the maximum distance to distinguish DSB clusters) of scoring DNA damage were studied to investigate the impact on the uncertainties of DNA damage. On the basis of comparison of our results with experimental data and published findings, we were able to accurately predict the yield of various types of DNA damage. Our results indicated that the difference in physics constructor can cause up to 56.4% in the DNA double-strand break (DSB) yields. The DSB yields were quite sensitive to the energy threshold for strand breaks (SB) and the maximum distance to classify the DSB clusters, which were even more than 100 times and four times than the default configurations, respectively.

Keywords: DNA damage; Geant4-DNA; Monte Carlo simulation; uncertainty analysis.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
MFP simulations for electrons in liquid water as a function of initial electron energy from 12 eV to 50 keV. (a) The total MFP simulations for option2, option2 with ELSEPA and opt2and4. (b) The total MFP simulations for option4, option4 with ELSEPA and opt2and4. (c) The total MFP simulation for option6, option6 with ELSEPA and opt2and4. (d) The inelastic MFP for the option with the ELSEPA model was calculated and compared with the experimental data adapted from Ref. [62] Ashley et al., 1988, and the value adapted from Ref. [63] Emfietzoglou et al., 2017.
Figure 2
Figure 2
Range simulations in water with different physics constructors as a function of primary electron energy from 10 eV to 1 MeV. (a) MCTS simulations of the total path length as a function of incident electron energy compared with the other MC simulations data adapted from Ref. [64] Wiklund et al., 2009, and Ref. [65] Wilson et al., 2014, and continuous-slowing-down-approximation (CSDA) methods data adapted from Ref. [66] Watt et al., 2004, and Ref. [67] Seltzer et al., 2016. (b) Variation of the electron penetration range in comparison with data adapted from Ref. [68] Meesungnoen et al., 2002, Ref. [69] Uehara et al., 2006, and Ref. [63] Emfietzoglou et al., 2017.
Figure 3
Figure 3
The dose-mean linear energy simulations for different scales of a chromatin simplified model (a−c).
Figure 4
Figure 4
Comparison of results for DNA damages obtained with Geant4-DNA with the experiment data adapted from Ref. [7] Leloup et al., 2005, Ref. [71] Frankenberg et al., 1999, and Ref. [72] Compa et al., 2005, and the simulated data adapted from Ref. [19] Friedland et al., 2010, and Ref. [70] Sakata et al., 2020. All simulations in this work used option2ELSEPA and the linear proportional model. (a) The ratio of SSB yield to DSB yield. (b) Total strand break (TSBs) yield for protons. (c) Total SSB yields for protons. (d) Total DSB yields for protons.
Figure 5
Figure 5
DNA damages simulation with various physics constructors. (a) The ratio of SSB yields to DSB yields. (b) The yield of SSB for various physics constructors. (c) The yield of DSB for various physics constructors.
Figure 6
Figure 6
Comparison of DNA damage obtained with different energy threshold model for SSBs. All results were simulated with the opt2ELSEPA model. (a) The ratio of DSBs to SSBs with different ET models. (b) The total yields for DSBs with different ET models. (c) Ratio of constant ET model with linear proportional model of 5−37.5 eV for the DSB/SSB ratio. (d) Ratio of constant ET model with linear proportional model of 5−37.5 eV for DSB yields.
Figure 7
Figure 7
DNA damage simulations with varying damage clustering distance. (a) The ratio of the yield of DSBs to the yield of SSBs. (b) The yield of DSBs as a function of incident proton energy with damage clustering distance of 3 bp, 10 bp, 30 bp and 40 bp. (c) The ratio for DSB/SSB of 10 bp results to other clustering distance used in this work. (d) The ratio for DSBs yield of 10 bp to other clustering distance.
Figure 8
Figure 8
Solenoid chromatin fiber model constructed with Geant4 toolkit. (a) Structure of B-DNA double helix. (b) Model of six nucleosomes. (c) Chromatin fiber geometry.
Figure 9
Figure 9
Schematic illustration of damage classification for the complexity of SSBs and DSBs, according to Nikjoo et al., The cube represents bases, the line represents sugar-phosphate backbones, and the circle represents damage points. (a) If only one SB occurs in one strand, it is classified as an SSB. (b) If more than one SSB occurs in the same strand, they are classified as SSB+. (c) If SBs are on both strands and separated by more than n base pair (bp), they are classified as 2 SSB. (d) If SBs are on opposite strands and separated by less than n bp, they are classified as a DSB. (e) If SBs have the same condition as a DSB and include an additional SSB, they are classified as DSB+. (f) If two or more DBSs are present in the segment, the SBs are classified as DSB++.
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