Simulations of deoxyribonucleic acid (DNA) molecular damage use the traversal algorithm that has the disadvantages of being time-consuming, slowly converging, and requiring high-performance computer clusters. This work presents an improved version of the algorithm, “density-based spatial clustering of applications with noise” (DBSCAN), using a KD-tree approach to find neighbors of each point for calculating clustered DNA damage. The resulting algorithm considers the spatial distributions for sites of energy deposition and hydroxyl radical attack, yielding the statistical probability of (single and double) DNA strand breaks. This work achieves high accuracy and high speed at calculating clustered DNA damage that has been induced by proton treatment at the molecular level while running on an i7 quad-core CPU. The simulations focus on the indirect effect generated by hydroxyl radical attack on DNA. The obtained results are consistent with those of other published experiments and simulations. Due to the array of chemical processes triggered by proton treatment, it is possible to predict the effects that different track structures of various energy protons produce on eliciting direct and indirect damage of DNA.
Simulation of Proton-Induced DNA Damage Patterns Using an Improved Clustering Algorithm
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Jing Tang, Qinfeng Xiao, Zhiguo Gui, Baosheng Li, Pengcheng Zhang; Simulation of Proton-Induced DNA Damage Patterns Using an Improved Clustering Algorithm. Radiat Res 2 October 2020; 194 (4): 363–378. doi: https://doi.org/10.1667/RR15552.1
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