Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins

Hydrogen atom transfer (HAT) reactions are important in many biological systems. As these reactions are hard to observe experimentally, it is of high interest to shed light on them using simulations. Here, we present a machine learning model based on graph neural networks for the prediction of energy barriers of HAT reactions in proteins. As input, the model uses exclusively non-optimized structures as obtained from classical simulations. It was trained on more than 17 000 energy barriers calculated using hybrid density functional theory. We built and evaluated the model in the context of HAT in collagen, but we show that the same workflow can easily be applied to HAT reactions in other biological or synthetic polymers. We obtain for relevant reactions (small reaction distances) a model with good predictive power (R2 ∼ 0.9 and mean absolute error of <3 kcal mol−1). As the inference speed is high, this model enables evaluations of dozens of chemical situations within seconds. When combined with molecular dynamics in a kinetic Monte-Carlo scheme, the model paves the way toward reactive simulations

Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins

Hydrogen atom transfer (HAT) reactions are important in many biological systems. As these reactions are hard to observe experimentally, it is of high interest to shed light on them using simulations. Here, we present a machine learning model based on graph neural networks for the prediction of energy barriers of HAT reactions in proteins. As input, the model uses exclusively non-optimized structures as obtained from classical simulations. It was trained on more than 17,000 energy barriers calculated using hybrid density functional theory. We built and evaluated the model in the context of HAT in collagen, but we show that the same workflow can easily be applied to HAT reactions in other biological or synthetic polymers. We obtain for relevant reactions (small reaction distances) a model with good predictive power (R2 ∼ 0.9 and mean absolute error of < 3 kcal/mol). As the inference speed is high, this model enables evaluations of dozens of chemical situations within seconds. When combined with molecular dynamics in a kinetic Monte-Carlo scheme, the model paves the way toward reactive simulations

Single-molecule localization microscopy as a promising tool for

Quantification and structural studies of DNA double strand breaks (DSBs) are an essential part of radiobiology because DSBs represent the most serious damage introduced to the DNA molecule by ionizing radiation. Although standard immunofluorescence confocal microscopy has demonstrated its usefulness in a large number of research studies, it lacks the resolution required to separate individual, closely associated DSBs, which appear after cell exposure to high linear energy transfer (high-LET) radiation and can be visualized as clusters or streaks of radiation-induced repair foci (IRIFs). This prevents our deeper understanding of DSB induction and repair. Recent breakthroughs in super-resolution light microscopy, such as the development of single-molecule localization microscopy (SMLM), offer an optical resolution of approximately an order of magnitude better than that of standard confocal microscopy and open new horizons in radiobiological research. Unlike electron microscopy, SMLM (also referred to as “nanoscopy”) preserves the natural structure of biological samples and is not limited to very thin sample slices. Importantly, SMLM not only offers a resolution on the order of approximately 10 nm, but it also provides entirely new information on the biochemistry and spatio-temporal organization of DSBs and DSB repair at the molecular level. Nevertheless, it is still challenging to correctly interpret these often surprising nanoscopy results. In the present article, we describe our first attempts to use SMLM to explore γH2AX and 53BP1 repair foci induced with 15N high-LET particles

Recruitment of 53BP1 Proteins for DNA Repair and Persistence of Repair Clusters Differ for Cell Types as Detected by Single Molecule Localization Microscopy

DNA double stranded breaks (DSBs) are the most serious type of lesions introduced into chromatin by ionizing radiation. During DSB repair, cells recruit different proteins to the damaged sites in a manner dependent on local chromatin structure, DSB location in the nucleus, and the repair pathway entered. 53BP1 is one of the important players participating in repair pathway decision of the cell. Although many molecular biology details have been investigated, the architecture of 53BP1 repair foci and its development during the post-irradiation time, especially the period of protein recruitment, remains to be elucidated. Super-resolution light microscopy is a powerful new tool to approach such studies in 3D-conserved cell nuclei. Recently, we demonstrated the applicability of single molecule localization microscopy (SMLM) as one of these highly resolving methods for analyses of dynamic repair protein distribution and repair focus internal nano-architecture in intact cell nuclei. In the present study, we focused our investigation on 53BP1 foci in differently radio-resistant cell types, moderately radio-resistant neonatal human dermal fibroblasts (NHDF) and highly radio-resistant U87 glioblastoma cells, exposed to high-LET 15N-ion radiation. At given time points up to 24 h post irradiation with doses of 1.3 Gy and 4.0 Gy, the coordinates and spatial distribution of fluorescently tagged 53BP1 molecules was quantitatively evaluated at the resolution of 10&#8315;20 nm. Clusters of these tags were determined as sub-units of repair foci according to SMLM parameters. The formation and relaxation of such clusters was studied. The higher dose generated sufficient numbers of DNA breaks to compare the post-irradiation dynamics of 53BP1 during DSB processing for the cell types studied. A perpendicular (90&#176;) irradiation scheme was used with the 4.0 Gy dose to achieve better separation of a relatively high number of particle tracks typically crossing each nucleus. For analyses along ion-tracks, the dose was reduced to 1.3 Gy and applied in combination with a sharp angle irradiation (10&#176; relative to the cell plane). The results reveal a higher ratio of 53BP1 proteins recruited into SMLM defined clusters in fibroblasts as compared to U87 cells. Moreover, the speed of foci and thus cluster formation and relaxation also differed for the cell types. In both NHDF and U87 cells, a certain number of the detected and functionally relevant clusters remained persistent even 24 h post irradiation; however, the number of these clusters again varied for the cell types. Altogether, our findings indicate that repair cluster formation as determined by SMLM and the relaxation (i.e., the remaining 53BP1 tags no longer fulfill the cluster definition) is cell type dependent and may be functionally explained and correlated to cell specific radio-sensitivity. The present study demonstrates that SMLM is a highly appropriate method for investigations of spatiotemporal protein organization in cell nuclei and how it influences the cell decision for a particular repair pathway at a given DSB site