# Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

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## Abstract

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## 1. Introduction

## 2. An Overview of the Methods Used in Nanoscale Simulations

#### 2.1. Particle Track Structure Codes

^{6}MeV/u). It is noteworthy that the TOPAS-nBio software [90], which extends the TOPAS MC code [91] to the (sub) cellular and DNA scale for radiobiological studies [92], is based on the Geant4-DNA package.

#### 2.2. Monte Carlo Techniques for Radiobiological Modelling

^{56}Fe), with kinetic energies up to a few GeV [102,103,104]. It also has the ability to simulate damage induction for random mixtures of charged particles. For photons and neutrons, MCDS can provide the distribution of secondary charged particles produced via the interaction of neutral particles with a target region of interest [115]. Considering the spectrum of energy used for the particles involved in MCDS, the minimum allowed kinetic energy limit depends on the particle type: e.g., for electrons, damage induction can be simulated from some tens of eV, while for bigger particles the corresponding limit increases with increasing atomic number. This code can also simulate the effects of oxygen on the induction of clustered DNA lesions. Because of the fact that MCDS provides simulations tacitly for both direct and indirect DNA damage mechanisms, it uses an extraneous free radical scavenger (DMSO) and thus imitates diminutions in the total amount of strand breaks and base damages because of the scavenger’s presence [102]. It must be mentioned at this point that MCDS simulates the so called “initial” levels of DNA damage induced and not the processing or repair.

#### 2.3. DNA Modelling

## 3. Monte Carlo Applications for Assessing Biological Damage

#### 3.1. Types of Irradiation techniques and Applications

^{−1}), produced by the electromagnetic interaction of radiation with matter, interact chemically with tissues, cells, and DNA. Moreover, IR can also be categorized by the energy loss of radiation per unit path length, called linear energy transfer (LET), which is an indicator of the resulting biological effect, to (a) high-LET and (b) low-LET radiation. It must be noted that some of the work with radiobiological modelling at the nanometer scale is to search for a way to characterize IR other than LET. It is important to point out that even though LET is widely used, it has limitations when it comes to characterizing IR in terms of biological outcome. More specifically, we refer to the shortcomings of the relative biological effectiveness (RBE) vs LET relationship due to broad LET distribution, as in a single spread-out Bragg peak (SOBP) or in multiple overlapping radiation fields as discussed in [129].

#### 3.2. Direct Damage Studies

#### 3.3. Water Radiolysis: Indirect Damage Studies

_{eff}/β)

^{2}to DNA strand breakage and the DNA fragmentation dependency to LET. Their results were compared with published data by the fast Monte Carlo damage simulation (MCDS) tool [103,104,131].

#### 3.4. DNA Damage Repair Simulation Techniques

#### 3.5. DNA Damage Quantification Techniques Other Than Monte Carlo

## 4. Conclusions and Future Prospects

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**Number of published articles, over the last 30 years, on “Monte Carlo simulations” for the investigation of “DNA damage”.

**Figure 2.**Particle transport example. (

**a**) Track structure of an electron (10 KeV) in water as simulated in Geant4-DNA. The red line, which starts from the bottom right edge, is the route followed by the primary electron, while in yellow the interactions with the water medium are presented. The red branches that are separated from the main route represent secondary electrons. (

**b**) Schematic representation of the way that energy is deposited on DNA molecules. This is a stylish representation, which has the aim of helping the reader understand the way that the superposition of energy deposition in water is transformed to single or double strand breaks. The blue edges imitate DNA bases.

**Figure 3.**3D view of two different DNA molecules by the Proteins Data Bank (PDB) database. Scale bars have been added accordingly. Both scale bars represent a distance of 30 nm. (

**a**) Simple small DNA, stylish view, (

**b**) simple small DNA, “simulation” view, (

**c**) complex DNA, stylish view, (

**d**) complex DNA, “simulation” view.

**Figure 4.**Induction of different types of DNA damage by ionizing radiation includes single and clustered forms of damage. This may often lead to misrepair.

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**MDPI and ACS Style**

Chatzipapas, K.P.; Papadimitroulas, P.; Emfietzoglou, D.; Kalospyros, S.A.; Hada, M.; Georgakilas, A.G.; Kagadis, G.C.
Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations. *Cancers* **2020**, *12*, 799.
https://doi.org/10.3390/cancers12040799

**AMA Style**

Chatzipapas KP, Papadimitroulas P, Emfietzoglou D, Kalospyros SA, Hada M, Georgakilas AG, Kagadis GC.
Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations. *Cancers*. 2020; 12(4):799.
https://doi.org/10.3390/cancers12040799

**Chicago/Turabian Style**

Chatzipapas, Konstantinos P., Panagiotis Papadimitroulas, Dimitris Emfietzoglou, Spyridon A. Kalospyros, Megumi Hada, Alexandros G. Georgakilas, and George C. Kagadis.
2020. "Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations" *Cancers* 12, no. 4: 799.
https://doi.org/10.3390/cancers12040799