Refine
Year of publication
Document Type
- Article (1867)
- Preprint (1244)
- Doctoral Thesis (593)
- Conference Proceeding (248)
- diplomthesis (101)
- Bachelor Thesis (75)
- Master's Thesis (61)
- Contribution to a Periodical (46)
- Book (33)
- Diploma Thesis (33)
Keywords
- Kollisionen schwerer Ionen (47)
- heavy ion collisions (44)
- LHC (25)
- Quark-Gluon-Plasma (25)
- Heavy Ion Experiments (20)
- equation of state (19)
- quark-gluon plasma (19)
- Relativistic heavy-ion collisions (16)
- QCD (15)
- QGP (15)
Institute
- Physik (4396) (remove)
The SLC26 family of transporters maintains anion equilibria in all kingdoms of life. The family shares a 7 + 7 transmembrane segments inverted repeat architecture with the SLC4 and SLC23 families, but holds a regulatory STAS domain in addition. While the only experimental SLC26 structure is monomeric, SLC26 proteins form structural and functional dimers in the lipid membrane. Here we resolve the structure of an SLC26 dimer embedded in a lipid membrane and characterize its functional relevance by combining PELDOR distance measurements and biochemical studies with MD simulations and spin-label ensemble refinement. Our structural model reveals a unique interface different from the SLC4 and SLC23 families. The functionally relevant STAS domain exerts a stabilizing effect on regions central in this dimer. Characterization of heterodimers indicates that protomers in the dimer functionally interact. The combined structural and functional data define the framework for a mechanistic understanding of functional cooperativity in SLC26 dimers.
Molecular mechanisms of inorganic-phosphate release from the core and barbed end of actin filaments
(2023)
The release of inorganic phosphate (Pi) from actin filaments constitutes a key step in their regulated turnover, which is fundamental to many cellular functions. However, the molecular mechanisms underlying Pi release from both the core and barbed end of actin filaments remain unclear. Here, we combine cryo-EM with molecular dynamics simulations and in vitro reconstitution to demonstrate how actin releases Pi through a ‘molecular backdoor’. While constantly open at the barbed end, the backdoor is predominantly closed in filament-core subunits and only opens transiently through concerted backbone movements and rotameric rearrangements of residues close to the nucleotide binding pocket. This mechanism explains why Pi escapes rapidly from the filament end and yet slowly from internal actin subunits. In an actin variant associated with nemaline myopathy, the backdoor is predominantly open in filament-core subunits, resulting in greatly accelerated Pi release after polymerization and filaments with drastically shortened ADP-Pi caps. This demonstrates that the Pi release rate from F-actin is controlled by steric hindrance through the backdoor rather than by the disruption of the ionic bond between Pi and Mg2+ at the nucleotide-binding site. Our results provide the molecular basis for Pi release from actin and exemplify how a single, disease-linked point mutation distorts the nucleotide state distribution and atomic structure of the actin filament.
Maximum likelihood estimates of diffusion coefficients from single-particle tracking experiments
(2021)
Single-molecule localization microscopy allows practitioners to locate and track labeled molecules in biological systems. When extracting diffusion coefficients from the resulting trajectories, it is common practice to perform a linear fit on mean-squared-displacement curves. However, this strategy is suboptimal and prone to errors. Recently, it was shown that the increments between the observed positions provide a good estimate for the diffusion coefficient, and their statistics are well-suited for likelihood-based analysis methods. Here, we revisit the problem of extracting diffusion coefficients from single-particle tracking experiments subject to static noise and dynamic motion blur using the principle of maximum likelihood. Taking advantage of an efficient real-space formulation, we extend the model to mixtures of subpopulations differing in their diffusion coefficients, which we estimate with the help of the expectation–maximization algorithm. This formulation naturally leads to a probabilistic assignment of trajectories to subpopulations. We employ the theory to analyze experimental tracking data that cannot be explained with a single diffusion coefficient. We test how well a dataset conforms to the assumptions of a diffusion model and determine the optimal number of subpopulations with the help of a quality factor of known analytical distribution. To facilitate use by practitioners, we provide a fast open-source implementation of the theory for the efficient analysis of multiple trajectories in arbitrary dimensions simultaneously.
The interaction between the Heat Shock Proteins 70 and 40 is at the core of the ATPase regulation of the chaperone machinery that maintains protein homeostasis. However, the structural details of the interaction remain elusive and contrasting models have been proposed for the transient Hsp70/Hsp40 complexes. Here we combine molecular simulations based on both coarse-grained and atomistic models with coevolutionary sequence analysis to shed light on this problem by focusing on the bacterial DnaK/DnaJ system. The integration of these complementary approaches resulted in a novel structural model that rationalizes previous experimental observations. We identify an evolutionarily conserved interaction surface formed by helix II of the DnaJ J-domain and a structurally contiguous region of DnaK, involving lobe IIA of the nucleotide binding domain, the inter-domain linker, and the β-basket of the substrate binding domain.
The interaction between the Heat Shock Proteins 70 and 40 is at the core of the ATPase regulation of the chaperone machinery that maintains protein homeostasis. However, the structural details of this fundamental interaction are still elusive and contrasting models have been proposed for the transient Hsp70/Hsp40 complexes. Here we combine molecular simulations based on both coarsegrained and atomistic models with co-evolutionary sequence analysis to shed light on this problem by focusing on the bacterial DnaK/DnaJ system. The integration of these complementary approaches resulted into a novel structural model that rationalizes previous experimental observations. We identify an evolutionary-conserved interaction surface formed by helix II of the DnaJ J-domain and a groove on lobe IIA of the DnaK nucleotide binding domain, involving the inter-domain linker.
TriMem: A parallelized hybrid Monte Carlo software for efficient simulations of lipid membranes
(2022)
Lipid membranes are integral building blocks of living cells and perform a multitude of biological functions. Currently, molecular simulations of cellular-scale membrane remodeling processes at atomic resolution are extremely difficult, due to their size, complexity, and the large times-scales on which these processes occur. Instead, elastic membrane models are used to simulate membrane shapes and transitions between them and to infer their properties and functions. Unfortunately, an efficiently parallelized open-source simulation code to do so has been lacking. Here, we present TriMem, a parallel hybrid Monte Carlo simulation engine for triangulated lipid membranes. The kernels are efficiently coded in C++ and wrapped with Python for ease-of-use. The parallel implementation of the energy and gradient calculations and of Monte Carlo flip moves of edges in the triangulated membrane enable us to simulate large and highly curved membrane structures. For validation, we reproduce phase diagrams of vesicles with varying surface-to-volume ratios and area difference. We also compute the density of states to verify correct Boltzmann sampling. The software can be used to tackle a range of large-scale membrane remodeling processes as a step toward cell-scale simulations. Additionally, extensive documentation make the software accessible to the broad biophysics and computational cell biology communities.
Abstract
The primary immunological target of COVID-19 vaccines is the SARS-CoV-2 spike (S) protein. S is exposed on the viral surface and mediates viral entry into the host cell. To identify possible antibody binding sites, we performed multi-microsecond molecular dynamics simulations of a 4.1 million atom system containing a patch of viral membrane with four full-length, fully glycosylated and palmitoylated S proteins. By mapping steric accessibility, structural rigidity, sequence conservation, and generic antibody binding signatures, we recover known epitopes on S and reveal promising epitope candidates for structure-based vaccine design. We find that the extensive and inherently flexible glycan coat shields a surface area larger than expected from static structures, highlighting the importance of structural dynamics. The protective glycan shield and the high flexibility of its hinges give the stalk overall low epitope scores. Our computational epitope-mapping procedure is general and should thus prove useful for other viral envelope proteins whose structures have been characterized.
Author summary
The SARS-CoV-2 virus has caused a global health crisis. The spike protein exposed at its surface is key for infection and the primary antibody target. However, spike is covered by highly mobile glycan molecules that could impair antibody binding. To identify accessible epitopes, we performed molecular dynamics simulations of an atomistic model of glycosylated spike embedded in a membrane. By combining extensive simulations with bioinformatics analyses, we recovered known antibody binding sites and identified several epitope candidates as targets for further vaccine development.
More than 75% of surface and secreted proteins are modified by covalent addition of complex sugars through N- and O-glycosylation. Unlike proteins, glycans do not typically adopt specific secondary structures and remain very mobile, influencing protein dynamics and interactions with other molecules. Glycan conformational freedom impairs complete structural elucidation of glycoproteins. Computer simulations may be used to model glycan structure and dynamics. However, such simulations typically require thousands of computing hours on specialized supercomputers, thus limiting routine use. Here, we describe a reductionist method that can be implemented on personal computers to graft ensembles of realistic glycan conformers onto static protein structures in a matter of minutes. Using this open-source pipeline, we reconstructed the full glycan cover of SARS-CoV-2 Spike protein (S-protein) and a human GABAA receptor. Focusing on S-protein, we show that GlycoSHIELD recapitulates key features of extended simulations of the glycosylated protein, including epitope masking, and provides new mechanistic insights on N-glycan impact on protein structural dynamics.
Transient receptor potential (TRP) ion channels are among the most well-studied classes of temperature-sensing molecules. Yet, the molecular mechanism and thermodynamic basis for the temperature sensitivity of TRP channels remains to this day poorly understood. One hypothesis is that the temperature-sensing mechanism can simply be described by a difference in heat capacity between the closed and open channel states. While such a two-state model may be simplistic it nonetheless has descriptive value, in the sense that it can be used to to compare overall temperature sensitivity between different channels and mutants. Here, we introduce a mathematical framework based on the two-state model to reliably extract temperature-dependent thermodynamic potentials and heat capacities from measurements of equilibrium constants at different temperatures. Our framework is implemented in an open-source data analysis package that provides a straightforward way to fit both linear and nonlinear van ‘t Hoff plots, thus avoiding some of the previous, potentially erroneous, assumptions when extracting thermodynamic variables from TRP channel electrophysiology data.
Seit hundert Jahren ist bekannt, dass die mikroskopische Welt der Atome und Moleküle von den Gesetzen der Quantenphysik regiert wird. Lange Zeit galten Quantenphänomene als verworren und unkontrollierbar. Heute arbeiten Physikerinnen und Physiker daran, unter Nutzung quantenphysikalischer Effekte Materialien mit neuartigen Eigenschaften zu kreieren.
Am Teilchenbeschleuniger in Darmstadt werden die extremen Bedingungen unseres Universums im Labor erforscht. Dabei gelang es den Physikerinnen und Physikern, eine Technologie zu entwickeln, die Energie zur Teilchenbeschleunigung wiederverwendet und einspart. Der Teilchenbeschleuniger ist eingebunden in das Clusterprojekt ELEMENTS, das gemeinsam von der Goethe-Universität Frankfurt und der TU Darmstadt geleitet wird.
Using 10.1 × 109 J/ψ events produced by the Beijing Electron Positron Collider (BEPCII) at a center-of-mass energy √s = 3.097 GeV and collected with the BESIII detector, we present a search for the rare semi-leptonic decay J/ψ → D−e+νe + c.c. No excess of signal above background is observed, and an upper limit on the branching fraction ℬ(J/ψ → D−e+νe + c. c.) < 7.1 × 10−8 is obtained at 90% confidence level. This is an improvement of more than two orders of magnitude over the previous best limit.
We derive the thermal noise spectrum of the longitudinal and transverse electric field operator of a given wave vector starting from the quantum-statistical definitions and relate it to the frequency and wave vector dependent complex conductivity in a homogeneous, isotropic system of electromagnetic interacting charged particles in the frame of the non-relativistic QED. No additional assumptions except the validity of linear response are used in the proof. The Nyquist formula for vanishing frequency, as well as the noise spectral density of Callen-Welton follow as byproduct. Furthermore we discuss also the noise of the photon occupation numbers.
As part of the research for this thesis, a momentum spectrometer was set up and initial measurements on accelerated ions were performed. For this purpose, the necessary hardware for the operation of the spectrometer and for high-precision measurements was were assembled. A control system for remote operation was developed and the spectrometer was installed at the used beamline.
There, measurements of low-energy ion beams in superposition with electrons confined in a Gabor lens can be carried out.
Investigations were made on both the Gabor lens-generated ions and the beam ions, leading to first results regarding the charge changes of beam ions during propagation through an electron atmosphere.
In order to understand the origin of the elements in the universe, one must understand the nuclear reactions by which atomic nuclei are transformed. There are many different astrophysical environments that fulfill the conditions of different nucleosynthesis processes. Even though great progress has been made in recent decades in understanding the origin of the elements in the universe, some questions remain unanswered. In order to understand the processes, it is necessary to measure cross sections of the involved reactions and constrain theoretical model predictions. A variety of methods have been developed to measure nuclear reaction cross sections relevant for nuclear astrophysics. In this thesis, two different experiments and their results, both using the well-established activation method, are presented.
A measurement of the proton capture cross section on the p-nuclide 96Ru was performed at the Institute of Structure and Nuclear Astrophysics ISNAP - Notre Dame, USA. The main goal of this experiment was to compare the results with those obtained by Mei et al. in a pioneering experiment using the method of inverse kinematics at the GSI Helmholtzzentrum für Schwerionenforschung GmbH - Darmstadt, Germany. Therefore, the activations were taken out at the same center of mass energies of 9 MeV, 10 MeV and 11 MeV. Another activation was taken out at an energy of 3.2 MeV to compare the result to a measurement of Bork et al. who also used the activation method. While the results at 3.2 MeV agree quite well with those of Bork et al., the results at higher energies show significantly smaller cross sections than those measured by Mei et al.. Experimental details, the data analysis and sources of uncertainties are discussed.
The second part of this thesis describes a neutron capture cross section experiment. At the Institut für Kernphysik - Goethe Universtität Frankfurt an experimental setup allows to produce quasi maxwell-distributed neutron fields to measure maxwell-averaged cross sections (MACS) relevant for s-process nucleosynthesis. The setup was upgraded by a fast electric linear guide to transport samples from the activation to the detection site. The cyclic activation of the sample allows to increase the signal-to-noise ratio and to measure neutron captures that lead to nuclei with
half-lives on the order of seconds. In a first campaign, MACS of the reactions 51V(n,γ), 107,109Ag(n,γ) and 103Rh(n,γ) were measured. The new components of the setup aswell as the data analysis framework are described and the results of the measurements are discussed.
We study the polarization of relativistic fluids using the relativistic density operator at global and local equilibrium. In global equilibrium, a new technique to compute exact expectation values is introduced, which is used to obtain the exact polarization vector for fields of any spin. The same result has been extended to the case of massless fields. Furthermore, it is demonstrated that at local equilibrium not only the thermal vorticity but also the thermal shear contribute to the polarization vector. It is shown that assuming an isothermal local equilibrium, the new term can solve the polarization sign puzzle in heavy ion collisions.
Using combined data from the Relativistic Heavy Ion and Large Hadron Colliders, we constrain the shear and bulk viscosities of quark-gluon plasma (QGP) at temperatures of ∼150–350 MeV. We use Bayesian inference to translate experimental and theoretical uncertainties into probabilistic constraints for the viscosities. With Bayesian model averaging we propagate an estimate of the model uncertainty generated by the transition from hydrodynamics to hadron transport in the plasma’s final evolution stage, providing the most reliable phenomenological constraints to date on the QGP viscosities.
Tracking influenza a virus infection in the lung from hematological data with machine learning
(2022)
The tracking of pathogen burden and host responses with minimal-invasive methods during respiratory infections is central for monitoring disease development and guiding treatment decisions. Utilizing a standardized murine model of respiratory Influenza A virus (IAV) infection, we developed and tested different supervised machine learning models to predict viral burden and immune response markers, i.e. cytokines and leukocytes in the lung, from hematological data. We performed independently in vivo infection experiments to acquire extensive data for training and testing purposes of the models. We show here that lung viral load, neutrophil counts, cytokines like IFN-γ and IL-6, and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models shows that blood granulocytes and platelets play a crucial role in prediction and are highly involved in the immune response against IAV. The proposed in silico tools pave the path towards improved tracking and monitoring of influenza infections and possibly other respiratory infections based on minimal-invasively obtained hematological parameters.