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Computational Molecular Physics of FKBPs and FRB-domain containing proteins
Get PDFProtein-protein interactions (PPIs) are fine-tuned dynamics essential to cells and their life cycles. In cancer,
deviations of these dynamics occur, leading to uncontrollable cell growth. The process of DNA repair is
particularly important here to preserve the genetic information inside our cells and to correct mutations that can lead to changes in cell dynamics.
DNA repair is a biological pathway often controlled by large proteins that recruit other proteins. This recruitment leads to a complex construct of molecules (protein complex) that performs the actual DNA repair.
The areas within the protein complex where proteins interact with each other are called protein-protein interfaces. Understanding these interfaces at the molecular level may enable us to develop new inhibitors that interfere with DNA repair processes in a controlled manner. Since it is assumed that increased resistance to radiation and chemotherapy can be explained by the increased DNA repair ability of tumors, such inhibitors would enable the treatment of previously resistant tumors.
For the prediction of the structure of protein complexes, both classical algorithms (docking) and state-of-the-art machine learning-based methods were used in this work. The generated complexes are used as input for molecular dynamics simulations (MD simulations) to gain a time-resolved insight into the molecular biophysics of these protein-protein interfaces.
The central recruiting proteins of DNA repair form a class of protein kinases that all contain a so-called FKBP Rapamycin Binding region (FRB region). In this context, FKBP stands for FK506 binding protein, a class of proteins defined by the binding of the small molecule FK506. The FRB region is a structural subunit of a protein to which FKBPs or Rapamycin binds.
The common feature of FKBPs is the existence of a structural region binding FK506. This region can also bind numerous other proteins instead of FK506. FKBPs are therefore associated with a variety of diseases and various inhibitors interfering with these proteins’ binding capabilities are being investigated as potential drugs.
This common feature is also one of the reasons why FKBPs can fulfill various functions in our body.
This thesis examines a series of protein complexes, each containing either a single FKBP or a protein with an FRB region. Additionally, complexes in which binding occurs between both proteins are also analyzed.
The central protein kinase of the non-homologous end joining (NHEJ) DNA repair pathway was chosen as a representative for a protein containing an FRB region without a linked FKBP: DNA-dependent protein kinase, catalytic subunit (DNA-PKcs). A series of protein complexes with DNA-PKcs were modeled in collaboration with experimenters. The modeling indicates the existence of a previously unknown protein complex consisting of, among others, two DNA-PKcs molecules, which explains previously published laboratory results.
Furthermore, the protein structure of the DNA-PKcs was resolved with AlphaFold v2 (AF2) for the first time.
Based on the resolved structure, the biophysics of the binding between DNA and DNA-PKcs were investigated in the context of the NHEJ repair mechanism.
Similar studies were carried out for an FKBP of L. pneumophila. This protein is associated with the virulence of the bacterium. Several experimentally proven protein complexes containing this FKBP were modeled. This fundamental research in collaboration with the Steinert group at the TU Braunschweig provides new insight
into how the virulence of L. pneumophila can be explained
HYDRA-TPC Prototype - a Time Projection Chamber for Light Hypernuclei Study at R³B, GSI/FAIR
Get PDFHypernuclei offer a unique approach to investigating hyperon-nucleon interactions. However, their extremely short lifetimes, on the order of sub-nanoseconds, pose significant experimental challenges. The HYpernuclei Decay at R³B Apparatus (HYDRA) experiment, designed for operation within the R³B setup at GSI/FAIR, aims to perform heavy-ion collision experiments with the primary objective of performing high-precision invariant mass spectroscopy of light hypernuclei.
This thesis presents the development of the HYDRA Time Projection Chamber (TPC) specifically designed for tracking π − produced from hypernuclear decays within the GLAD magnet of the R³B. The TPC incorporates a double-layer wired drift field cage with a drift distance of 300 mm and an active area of 256 × 88 mm2. A hybrid amplification stage was implemented, comprising a Gas Electron Multiplier (GEM) and a Micromegas detector. This configuration is expected to achieve an ion back-flow of less than 1%.
The design of the field cage was optimized through two-dimensional simulations employing the finite element method and Monte Carlo techniques to ensure a homogeneous drift field. Electron drift displacement was determined to be less than 250 µm at the edge of the active region and less than 200 µm in the central region
of the TPC.
The gain performance of the TPC was characterized using an X-ray source. By adjusting the high voltage applied to the electrodes, the influence of varying high voltages in different regions on the overall effective gain of the TPC was quantified.
The TPC was successfully commissioned with a front-end readout system incorporating multiplexing boards and digitizing readout electronics based on the GET system. Subsequently, its tracking performance was assessed through measurements of laser tracks generated by a 266-nm ultraviolet laser source and reflected into the drift volume by micromirror bundles, which were integrated within the TPC. A tracking algorithm was developed to reconstruct these laser tracks. Experimental results demonstrated a spatial resolution better than 3 mm in the drift direction, while the pad plane resolution did not meet the desired 200 µm requirement.
Finally, the influence of magnetic fields on the drift electron trajectories was investigated within the GLAD magnet at magnetic field strengths ranging from 0 to 0.92 T
Fluidized bed gasification of plastic waste and residual biomass – an overview of HTW® and Chemical looping technology development
Get PDFMechanical recycling of plastic waste to second generation products is the currently mostly applied technology to reuse the valuable elements contained, particularly carbon, but often leads to a loss in product quality. Furthermore, its economic potential is limited due to heterogeneous waste streams, and the remainder - non-recyclable composites - is disposed in landfills or thermally utilized with the challenge of carbon capture. In contrast, chemical recycling preserves the carbon and other elements such as hydrogen by transforming them into valuable base chemicals or synthetic fuels. This enables a circular economy, which is a key factor in achieving a net-zero emission society. Thus, the Institute for Energy Systems and Technology at the Technical University of Darmstadt is investigating the promising path of fluidized bed gasification processes with downstream gas cleaning and synthesis at pilot scale. Its 1 MWth modular pilot plant allows for different process configurations as bubbling bed, circulating bed and dual-fluidized bed gasification under autothermal conditions. The whole process chain from the waste to a valuable product such as methanol or Fischer-Tropsch has been demonstrated and optimized in test campaigns of several weeks. Based on these pilot tests, an upscaling to industrial scale is conducted in combination with modelling and simulation. Expertise has been built up from 2015 in the High-Temperature Winkler (HTW®) gasification of lignite, where meanwhile residual feedstock as biomass and plastic waste (solid recovered fuel = SRF) have been proven to be suitable. Chemical looping gasification (CLG) was demonstrated successfully and investigated for the first time at pilot scale in 2022 at the institute using biogenic residues as feedstock
Being in Two Spaces: Investigating and Mitigating Spatial Conflicts in Virtual Reality
Get PDFVirtual Reality (VR) allows people to immerse themselves in a computer-mediated environment. When interacting in VR, a person mainly sees the virtual environment and is visually disconnected from the physical space. However, this person is still physically interacting within the physical space—the experience of using VR occurs in two spaces. Simultaneously interacting with both the virtual and the physical
space can lead to accidents, such as colliding with obstacles, like furniture or bystanders. Especially since VR technology has become more prominent in diverse physical spaces, such as during transportation, at home, or outdoors, the chance of accidents and collisions increases, negatively affecting the VR experience. I refer to this phenomenon as a spatial conflict caused by a misalignment between two spaces,
disrupting the VR experience. To enhance the safety of VR interaction, more knowledge is needed to identify different types of spatial conflicts, understand how they form in the VR experience, and develop mitigation guidelines. I define two categories of spatial conflicts: (1) cognitive spatial conflicts which may occur in the cognitive process when a person updates spatial or body representations, and (2) action spatial conflicts which are caused by the actions of people while using
VR. First, I conducted one lab study, demonstrating that cognitive spatial conflicts can occur when updating spatial representations and affect the sense of presence. Through one lab and two online studies, I showed that when experiencing a virtual body, cognitive spatial conflicts can negatively affect the judgment of body ownership. For
action spatial conflicts, I investigated collisions with the physical space by identifying behaviors and reasons for how people interact with the VR safety boundary through an online survey and lab study. Further, I developed an interaction technique (FingerMapper) to reduce collisions while using VR in a confined physical space. Through a speculative design process, I explored how action spatial conflicts may occur in future VR scenarios and derived mitigation guidelines. Based on my findings, I discuss alternative types of conflicts, how to enhance VR safety, and implications for the definition of presence. Finally, I identify two major challenges for future research: mitigating spatial conflicts in collaborative VR scenarios and developing computational
models to further understand cognitive strategies when people interact in two spaces. This thesis contributes a better understanding of spatial conflicts in VR and their mitigation, consisting of (1) empirical evidence for cognitive spatial conflicts during spatial updating and the formation of body-ownership judgments, (2) empirical evidence for action spatial conflicts by identifying behaviors and strategies of how people interact with the VR safety boundary and obstacles, and (3) mitigation guidelines and an interaction technique (FingerMapper) for action spatial conflicts
From a P‐Bridging Phosphaketene to μ‐Phosphinidenide and μ‐Diphosphaurea Units at a Dinickel Core
Get PDFSalt metathesis of dinickel(II) complex LNi₂Br (1; L is a dinucleating pyrazolate ligand with two β‐diketiminato chelate arms) with Na(OCP) ⋅ (dioxane)₂.₅ yielded LNi₂(PCO) (2) with a P‐bridging phosphaethynolate. Further reaction of 2 with benzyl isocyanide or with an N‐heterocyclic carbene (NHC) triggered decarbonylation and gave LNi₂(PCN‐CH₂Ph) (3) and LNi₂P(NHC) (4) with P‐bridging cyanophosphide and NHC‐phosphinidenide, respectively. Electronic structure analysis indicated a μ₂‐η² : η¹ binding mode of the PCO⁻ anion between the two NiII ions in 2, which is even more pronounced for the [PCN(−CH₂Ph)]⁻ anion in 3. DFT assessment of the formation mechanism of 4 showed that attack at the phosphaketene‐C atom is kinetically preferred but reversible and unproductive, while kinetically more demanding back‐side SN2 attack at the phosphaketene‐P atom triggers CO release with 4 as thermodynamic product. Nucleophilic addition at the phosphaketene‐C could be demonstrated by the strongly exergonic reaction of 2 with KPPh₂, giving unstable K[LNi₂(P(O)CPPh₂)] (5) with a P‐bridging and K⁺‐stabilized diphosphaurea derivative. All new complexes 2–5 have been comprehensively characterized, including by X‐ray diffraction
Differential effect of grassland mowing on arthropod taxa
Get PDF1. Arthropods face a global decline attributed to habitat loss, climate change, pesticide use, and an intensification of land‐use practices such as mowing. Studies on the effects of mowing on arthropod abundance showed conflicting results potentially due to multiple factors, including study design, grassland management, sampling method, and arthropod taxon studied.
2. We conducted four studies in different grasslands, including intensively and extensively used agricultural and urban grasslands, utilising sweep netting, suction sampling, and pitfall traps. We compared the mowing responses of arthropod taxa between those studies at three different taxonomic resolutions (first‐level overall arthropods, second‐level orders, and third‐level families and suborders).
3. First, we discovered that mowing had a negative effect on overall arthropod abundance in all our studies (first level). Second, our four studies found that seven second‐ and third‐level taxa showed only negative, four only positive, and four mixed positive and negative responses. Third, regarding taxonomic resolution, no third‐level taxon reacted differently to mowing compared to the second‐level taxon it belongs to.
4. Our results indicate that for some taxa, mowing has a consistent negative (e.g. Diptera) or positive effects (e.g. Coleoptera). We suggest those groups have uniform phenological traits that make them especially vulnerable to mowing. For taxa showing mixed responses, we expect that study‐dependent factors such as region, sampling method, and grassland management affect their response to mowing
Machine Learning–Assisted Risk Assessment of Pitting Corrosion Susceptibility of AA1050 in Ethanol‐Containing Fuels
Get PDFThe ability to assess the risk of corrosion of metallic structures in particular environments holds considerable significance in the field of automotive industry. In recent years, machine learning has evolved into a crucial tool to evaluate the complex and multidimensional corrosion phenomena. In this paper, the special case of non‐aqueous alcoholate pitting corrosion of AA1050 in ethanol‐blended fuels with water and chloride contamination is examined via supervised machine learning techniques in order to distinguish between safe and unsafe conditions. The data space was created by conducting dedicated experiments with varying ethanol–fuel–water ratios, temperatures, and surface preparations. The classifier's performance rating of 0.87 (balanced accuracy) indicates an outstanding predictive ability and highlights the model's usefulness as decision support for subsequent experiments
A Contribution to Improving Baseflow Modeling in Low Mountain Ranges
Get PDFBaseflow is a vital component of the water balance of a catchment. Its consideration in integrated water resources management is important as it impacts the water quality and water temperature, as well as sustains the flow in rivers and streams during dry periods. Therefore, it is an essential ecological factor. Climate change will negatively affect baseflow, e.g., the amount of baseflow, in many catchments in the future. Low mountain ranges are especially at risk of increased water stress and consequent social-economic conflicts due to climate change. Unfortunately, baseflow is difficult to measure. Therefore, a plethora of methods exists to estimate baseflow from observations of total flow.
However, these methods cannot make predictions for future scenarios, taking climate change and anthropogenic impacts into consideration. For this reason, hydrological models, which simulate the rainfall runoff process in a catchment, are important tools for the investigation of future scenarios for operational planning. The aim of this thesis is to improve the modeling of baseflow in low mountain ranges with hydrological models. To this end, a study is conducted in a field laboratory in the Fischbach catchment in Hesse, Germany, which is a typical catchment in the German low mountain range. A conductivity mass balance method, recursive digital filters, as well as non-continuous separation
methods are evaluated in the Fischbach catchment. The hydrological model BlueM.Sim is used in this study as it is representative of typical hydrological models, e.g., SWAT and HEC-HMS. The main findings
of this study are:
1. The conductivity mass balance baseflow separation method is applicable in low mountain ranges. The months June to September and November to May are best suited for the estimation of the electric conductivity of the baseflow and quick flow components,
respectively. Both weekly and continuous monitoring are suited for the estimation of the electric conductivity of these components.
2. The Eckhardt filter, with a calibrated BFI max parameter, is recommended for continuous baseflow separation in low mountain ranges. The Kille method is recommended for the calibration of the BFI max parameter.
3. The physically based soil moisture approach in the current state of BlueM.Sim was able to reproduce the hydrological characteristics of the Fischbach catchment. At a daily timescale, periods are evident in which the modeled recessions do not match the observed recessions due to the single linear reservoir not being the optimal baseflow model structure in low mountain ranges. A direct calibration with baseflow time series is not possible in the current state of BlueM.Sim.
4. Simulated total flow duration curves of the conceptual monthly factor-based approach for baseflow modeling can agree very well with those of observed total flow. However, for successful validation, a solution had to be chosen that less consistently reproduced the flow
duration curve in the calibration period. The current factor-based approach is only applicable for the representation of long-term average conditions.
5. The greater data requirements, longer computation time and complex calibration of the soil moisture approach make it unfeasible for widespread use in operational planning. The factor-based approach may be a suitable compromise regarding data requirements, computation
time and calibration requirements.
6. The implementation of a stepwise calibration significantly improved the physical plausibility of model results, especially regarding baseflow.
7. The implementation of a parallel linear reservoir baseflow model in the soil moisture approach significantly improved the model results regarding baseflow. Parallel linear reservoirs are the superior model structure for baseflow modeling in low mountain ranges, regardless of
calibration strategy.
8. The novel modified factor approach significantly improved baseflow modeling with this conceptual approach. Unlike the original factor approach, this approach can represent different hydrological conditions. Therefore, this approach is of great interest for operational
planning.
9. The methodology of the hydrological model evaluation mostly fulfills the requirements of a comprehensive evaluation test as suggested in the literature. Therefore, this strongly suggests the suitability of BlueM.Sim for impact studies due to climate change
Muscular responses to upper body mediolateral angular momentum perturbations during overground walking
Get PDFAdaptive motor control and seamless coordination of muscle actions in response to external perturbations are crucial to maintaining balance during bipedal locomotion. There is an ongoing debate about the specific roles of individual muscles and underlying neural control circuitry that humans employ to maintain balance in different perturbation scenarios. To advance our understanding of human motor control in perturbation recovery, we conducted a study using a portable Angular Momentum Perturbator (AMP). Unlike other push/pull perturbation systems, the AMP can generate perturbation torques on the upper body while minimizing the perturbing forces at the center of mass. In this study, ten participants experienced trunk perturbations during either the mid-stance or touchdown phase in two frontal plane directions (ipsilateral and contralateral). We recorded and analyzed the electromyography (EMG) activity of eight lower-limb muscles from both legs to examine muscular responses in different phases and directions. Based on our findings, individuals primarily employ long-latency hip strategies to effectively counteract perturbation torques, with the occasional use of ankle strategies. Furthermore, it was found that proximal muscles, particularly the biarticular Rectus Femoris, consistently exhibited higher activation levels than other muscles. Additionally, in instances where a statistically significant difference was noted, we observed that the fastest reactions generally stem from muscles in close proximity to the perturbation site. However, the temporal sequence of muscles’ activation depends on the timing and direction of the perturbation. These findings enhance reflex response modeling, aiding the development of simulation tools for accurately predicting exogenous disturbances. Additionally, they hold the potential to shape the development of assistive devices, with implications for clinical interventions, particularly for the elderly
Smart sheet metal forming: importance of data acquisition, preprocessing and transformation on the performance of a multiclass support vector machine for predicting wear states during blanking
Get PDFIn consequence of high cost pressure and the progressive globalization of markets, blanking, which represents the most economical process in the value chain of manufacturing companies, is particularly dependent on reducing machine downtimes and increasing the degree of utilization. For this purpose, it is necessary to be able to make a real-time prediction about the current and future process conditions even at high production rates. Therefore, this study investigates the influence of data acquisition, preprocessing and transformation on the performance of a multiclass support vector machine to classify abrasive wear states during blanking based on force signals. The performance of the model was quantitatively evaluated based on the model accuracy and the separability of the classes. As a result, it was shown, that the deviation of time series represents the key parameter for the resulting performance of the classification model and strongly depends on the sensor type and position, the preprocessing procedure as well as the feature extraction and selection. Furthermore, it is shown that the consideration of domain knowledge in the phases of data acquisition, preprocessing and transformation improves the performance of the classification model and is essential to successfully implement AI projects. Summarizing the findings of this study, trustworthy data sets play a crucial role for implementing an automated process monitoring as a basis for resilient manufacturing systems