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Accessing radiation damage to biomolecules on the nanoscale by particle-scattering simulations
(2023)
Radiation damage to DNA plays a central role in radiation therapy to cure cancer. The physico-chemical and biological processes involved encompass huge time and spatial scales. To obtain a comprehensive understanding on the nano and the macro scale is a very challenging tasks for experimental techniques alone. Therefore particle-scattering simulations are often applied to complement measurements and aide their interpretation, to help in the planning of experiments, to predict their outcome and to test damage models. In the last years, powerful multipurpose particle-scattering framework based on the Monte-Carlo simulation (MCS) method, such as Geant4 and Geant4-DNA, were extended by user friendly interfaces such as TOPAS and TOPAS-nBio. This shifts their applicability from the realm of dedicated specialists to a broader range of scientists. In the present review we aim to give an overview over MCS based approaches to understand radiation interaction on a broad scale, ranging from cancerous tissue, cells and their organelles including the nucleus, mitochondria and membranes, over radiosensitizer such as metallic nanoparticles, and water with additional radical scavenger, down to isolated biomolecules in the form of DNA, RNA, proteins and DNA-protein complexes. Hereby the degradation of biomolecules by direct damage from inelastic scattering processes during the physical stage, and the indirect damage caused by radicals during the chemical stage as well as some parts of the early biological response is covered. Due to their high abundance the action of hydroxyl radicals (•OH) and secondary low energy electrons (LEE) as well as prehydrated electrons are covered in additional detail. Applications in the prediction of DNA damage, DNA repair processes, cell survival and apoptosis, influence of radiosensitizer on the dose distribution within cells and their organelles, the study of linear energy transfer (LET), the relative biological effectiveness (RBE), ion beam cancer therapy, microbeam radiation therapy (MRT), the FLASH effect, and the radiation induced bystander effect are reviewed.
A versatile software package in the form of a Python extension, named CDEF (computing Debye’s scattering formula for extraordinary form factors), is proposed to calculate approximate scattering profiles of arbitrarily shaped nanoparticles for small-angle X-ray scattering (SAXS). CDEF generates a quasi-randomly distributed point cloud in the desired particle shape and then applies the open-source software DEBYER for efficient evaluation of Debye’s scattering formula to calculate the SAXS pattern (https://github.com/j-from-b/CDEF). If self-correlation of the scattering signal is not omitted, the quasi-random distribution provides faster convergence compared with a true-random distribution of the scatterers, especially at higher momentum transfer. The usage of the software is demonstrated for the evaluation of scattering data of Au nanocubes with rounded edges, which were measured at the four-crystal monochromator beamline of PTB at the synchrotron radiation facility BESSY II in Berlin. The implementation is fast enough to run on a single desktop computer and perform model fits within minutes. The accuracy of the method was analyzed by comparison with analytically known form factors and verified with another implementation, the SPONGE, based on a similar principle with fewer approximations. Additionally, the SPONGE coupled to McSAS3 allows one to retrieve information on the uncertainty of the size distribution using a Monte Carlo uncertainty estimation algorithm.
Dose enhancement by gold nanoparticles (AuNP) increases the biological effectiveness of Radiation damage in biomolecules and tissue. To apply them effectively during cancer therapy their influence on the locally delivered dose has to be determined. Hereby, the AuNP locations strongly influence the energy deposit in the nucleus, mitochondria, membrane and the cytosol of the targeted cells. To estimate these effects, particle scattering simulations are applied. In general, different approaches for modeling the AuNP and their distribution within the cell are possible. In this work, two newly developed continuous and discrete-geometric models for simulations of AuNP in cells are presented.
These models are applicable to simulations of internal emitters and external radiation sources. Most of the current studies on AuNP focus on external beam therapy. In contrast, we apply the presented models in Monte-Carlo particle scattering simulations to characterize the energy deposit in cell organelles by radioactive 198AuNP. They emit beta and gamma rays and are therefore considered for applications with solid tumors. Differences in local dose enhancement between randomly distributed and nucleus targeted nanoparticles are compared. Hereby nucleus targeted nanoparticels showed a strong local dose enhancement in the radio sensitive nucleus. These results are the foundation for future experimental work which aims to obtain a mechanistic understanding of cell death induced by radioactive 198Au.
Supramolecular copolymerization driven by integrative self-sorting of hydrogen-bonded rosettes
(2020)
Molecular recognition to preorganize noncovalently polymerizable supramolecular complexes is a characteristic process of natural supramolecular polymers, and such recognition processes allow for dynamic self-alteration, yielding complex polymer systems with extraordinarily high efficiency in their targeted function. We herein show an example of such molecular recognition-controlled kinetic assembly/disassembly processes within artificial supramolecular polymer systems using six-membered hydrogen-bonded supramolecular complexes (rosettes). Electron-rich and poor monomers are prepared that kinetically coassemble through a temperature-controlled protocol into amorphous coaggregates comprising a diverse mixture of rosettes. Over days, the electrostatic interaction between two monomers induces an integrative self-sorting of rosettes. While the electron-rich monomer inherently forms toroidal homopolymers, the additional electrostatic interaction that can also guide rosette association allows helicoidal growth of supramolecular copolymers that are comprised of an alternating array of two monomers. Upon heating, the helicoidal copolymers undergo a catastrophic transition into amorphous coaggregates via entropy-driven randomization of the monomers in the rosette.
The movement of the macroscopic magnetic moment in ferromagnetic systems can be described by the Landau-Lifshitz (LL) or Landau-Lifshitz-Gilbert (LLG) equation. These equations are strictly valid only at absolute zero temperature. To include temperature effects a stochastic version of the LL or LLG equation for a spin density of one per unit cell can be used instead. To apply the stochastic LL to micromagnetic simulations, where the spin density per unit cell is generally higher, a conversion regarding simulation cell size and temperature has to be established. Based on energetic considerations, a conversion for ferromagnetic bulk and thin film systems is proposed. The conversion is tested in micromagnetic simulations which are performed with the Object Oriented Micromagnetic Framework (OOMMF). The Curie temperatures of bulk Nickel, Cobalt and Iron systems as well as Nickel thin-film systems with thicknesses between 6.3 mono layer (ML) and 31ML are determined from micromagnetic simulations. The results show a good agreement with experimentally determined Curie temperatures of bulk and thin film systems when temperature scaling is performed according to the presented model.