Peter, Christine
0000-0002-1471-5440 Berufsbeschreibung
Nachname
Vorname
Name
Suchergebnisse Publikationen
Specifying conformational heterogeneity of multi-domain proteins at atomic resolution
The conformational landscape of multi-domain proteins is inherently linked to their specific functions. This also holds for polyubiquitin chains that are assembled by two or more ubiquitin domains connected by a flexible linker thus showing a large interdomain mobility. However, molecular recognition and signal transduction are associated with particular conformational substates that are populated in solution. Here, we apply high-resolution NMR spectroscopy in combination with dual-scale MD simulations to explore the conformational space of K6-, K29-, and K33-linked diubiquitin molecules. The conformational ensembles are evaluated utilizing a paramagnetic cosolute reporting on solvent exposure plus a set of complementary NMR parameters. This approach unravels a conformational heterogeneity of diubiquitins and explains the diversity of structural models that have been determined for K6-, K29-, and K33-linked diubiquitins in free and ligand-bound states so far. We propose a general application of the approach developed here to demystify multi-domain proteins occurring in nature.
On the Binding Mechanisms of Calcium Ions to Polycarboxylates: Effects of Molecular Weight, Side Chain, and Backbone Chemistry
We experimentally determined the characteristics and Langmuir parameters of the binding of calcium ions to different polycarboxylates. By using potentiometric titrations and isothermal titration calorimetry, the effects of side chain chemistry, pH value, and chain length were systematically investigated using the linear polymers poly(aspartic acid), poly(glutamic acid), and poly(acrylic acid). We demonstrate that for polymers with high polymerization degrees, the binding process is governed by higher-order effects, such as the change of apparent pKa of carboxyl groups, and contributions arising from the whole polymer chain while the chemistry of the monomer unit constituting the polymer plays a subordinate role. In addition, primary binding sites need to be present in the polymer, thus rendering the abundance and sequential arrangement of protonated and deprotonated groups important. The detection of higher-order effects contradicts the assumptions posed by the Langmuir model of noninteracting binding sites and puts a question mark on whether ion binding to polycarboxylates can be described using solely a Langmuir binding model. No single uniform mechanism fits all investigated systems, and the whole polymer chain, including terminal groups, needs to be considered for the interpretation of binding data. Therefore, one needs to be careful when explaining ion binding to polymers solely based on studies on monomers or oligomers.
Three Reasons Why Aspartic Acid and Glutamic Acid Sequences Have a Surprisingly Different Influence on Mineralization
Understanding the role of polymers rich in aspartic acid (Asp) and glutamic acid (Glu) is the key to gaining precise control over mineralization processes. Despite their chemical similarity, experiments revealed a surprisingly different influence of Asp and Glu sequences. We conducted molecular dynamics simulations of Asp and Glu peptides in the presence of calcium and chloride ions to elucidate the underlying phenomena. In line with experimental differences, in our simulations, we indeed find strong differences in the way the peptides interact with ions in solution. The investigated Asp pentapeptide tends to pull a lot of ions into its vicinity, and many structures with clusters of calcium and chloride ions on the surface of the peptide can be observed. Under the same conditions, comparatively fewer ions can be found in proximity of the investigated Glu pentapeptide, and the structures are characterized by single calcium ions bound to multiple carboxylate groups. Based on our simulation data, we identified three reasons contributing to these differences, leading to a new level of understanding additive-ion interactions.
Deciphering molecular details of the RAC-ribosome interaction by EPR spectroscopy
The eukaryotic ribosome-associated complex (RAC) plays a significant role in de novo protein folding. Its unique interaction with the ribosome, comprising contacts to both ribosomal subunits, suggests a RAC-mediated coordination between translation elongation and co-translational protein folding. Here, we apply electron paramagnetic resonance (EPR) spectroscopy combined with site-directed spin labeling (SDSL) to gain deeper insights into a RAC-ribosome contact affecting translational accuracy. We identified a local contact point of RAC to the ribosome. The data provide the first experimental evidence for the existence of a four-helix bundle as well as a long α-helix in full-length RAC, in solution as well as on the ribosome. Additionally, we complemented the structural picture of the region mediating this functionally important contact on the 40S ribosomal subunit. In sum, this study constitutes the first application of SDSL-EPR spectroscopy to elucidate the molecular details of the interaction between the 3.3 MDa translation machinery and a chaperone complex.
Visualizing the Residue Interaction Landscape of Proteins by Temporal Network Embedding
Characterizing the structural dynamics of proteins with heterogeneous conformational landscapes is crucial to understanding complex biomolecular processes. To this end, dimensionality reduction algorithms are used to produce low-dimensional embeddings of the high-dimensional conformational phase space. However, identifying a compact and informative set of input features for the embedding remains an ongoing challenge. Here, we propose to harness the power of Residue Interaction Networks (RINs) and their centrality measures, established tools to provide a graph theoretical view on molecular structure. Specifically, we combine the closeness centrality, which captures global features of the protein conformation at residue-wise resolution, with EncoderMap, a hybrid neural-network autoencoder/multidimensional-scaling like dimensionality reduction algorithm. We find that the resulting low-dimensional embedding is a meaningful visualization of the residue interaction landscape that resolves structural details of the protein behavior while retaining global interpretability. This feature-based graph embedding of temporal protein graphs makes it possible to apply the general descriptive power of RIN formalisms to the analysis of protein simulations of complex processes such as protein folding and multidomain interactions requiring no protein-specific input. We demonstrate this on simulations of the fast folding protein Trp-Cage and the multidomain signaling protein FAT10. Due to its generality and modularity, the presented approach can easily be transferred to other protein systems.
Solvent-mediated Isotope Effects Strongly Influence the Early Stages of Calcium Carbonate Formation : Exploring D2O vs. H2O in a Combined Computational and Experimental Approach
In experimental studies, heavy water (D2O) is employed, e.g., so as to shift the spectroscopic solvent background, but any potential effects of this solvent exchange on reaction pathways are often neglected. While the important role of light water (H2O) during the early stages of calcium carbonate formation has been realized, studies into the actual effects of aqueous solvent exchanges are scarce. Here, we present a combined computational and experimental approach to start to fill this gap. We extended a suitable force field for molecular dynamics (MD) simulations. Experimentally, we utilised advanced titration assays and time-resolved attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. We find distinct effects in various mixtures of the two aqueous solvents, and in pure H2O or D2O. Disagreements between the computational results and experimental data regarding the stabilities of ion associates might be due to the unexplored role of HDO, or an unprobed complex phase behaviour of the solvent mixtures in the simulations. Altogether, however, our data suggest that calcium carbonate formation might proceed “more classically” in D2O. Also, there are indications for the formation of new structures in amorphous and crystalline calcium carbonates. There is huge potential towards further improving the understanding of mineralization mechanisms by studying solvent-mediated isotope effects, also beyond calcium carbonate. Last, it must be appreciated that H2O and D2O have significant, distinct effects on mineralization mechanisms, and that care has to be taken when experimental data from D2O studies are used, e.g., for the development of H2O-based computer models.
Guanidine-II aptamer conformations and ligand binding modes through the lens of molecular simulation
Regulation of gene expression via riboswitches is a widespread mechanism in bacteria. Here, we investigate ligand binding of a member of the guanidine sensing riboswitch family, the guanidine-II riboswitch (Gd-II). It consists of two stem-loops forming a dimer upon ligand binding. Using extensive molecular dynamics simulations we have identified conformational states corresponding to ligand-bound and unbound states in a monomeric stem-loop of Gd-II and studied the selectivity of this binding. To characterize these states and ligand-dependent conformational changes we applied a combination of dimensionality reduction, clustering, and feature selection methods. In absence of a ligand, the shape of the binding pocket alternates between the conformation observed in presence of guanidinium and a collapsed conformation, which is associated with a deformation of the dimerization interface. Furthermore, the structural features responsible for the ability to discriminate against closely related analogs of guanidine are resolved. Based on these insights, we propose a mechanism that couples ligand binding to aptamer dimerization in the Gd-II system, demonstrating the value of computational methods in the field of nucleic acids research.
Generating a conformational landscape of ubiquitin chains at atomistic resolution by back-mapping based sampling
Ubiquitin chains are flexible multidomain proteins that have important biological functions in cellular signalling. Computational studies with all-atom molecular dynamics simulations of the conformational spaces of polyubiquitins can be challenging due to the system size and a multitude of long-lived meta-stable states. Coarse graining is an efficient approach to overcome this problem—at the cost of losing high-resolution details. Recently, we proposed the back-mapping based sampling (BMBS) approach that reintroduces atomistic information into a given coarse grained (CG) sampling based on a two-dimensional (2D) projection of the conformational landscape, produces an atomistic ensemble and allows to systematically compare the ensembles at the two levels of resolution. Here, we apply BMBS to K48-linked tri-ubiquitin, showing its applicability to larger systems than those it was originally introduced on and demonstrating that the algorithm scales very well with system size. In an extension of the original BMBS we test three different seeding strategies, i.e. different approaches from where in the CG landscape atomistic trajectories are initiated. Furthermore, we apply a recently introduced conformational clustering algorithm to the back-mapped atomistic ensemble. Thus, we obtain insight into the structural composition of the 2D landscape and illustrate that the dimensionality reduction algorithm separates different conformational characteristics very well into different regions of the map. This cluster analysis allows us to show how atomistic trajectories sample conformational states, move through the projection space and in sum converge to an atomistic conformational landscape that slightly differs from the original CG map, indicating a correction of flaws in the CG template.
Multiscale simulations of protein and membrane systems
Classical multiscale simulations are perfectly suited to investigate biological soft matter systems. Owing to the bridging between microscopically realistic and lower-resolution models or the integration of a hierarchy of subsystems, one gets access to biologically relevant system sizes and timescales. In recent years, increasingly complex systems and processes have come into focus such as multidomain proteins, phase separation processes in biopolymer solutions, multicomponent biomembranes, or multiprotein complexes up to entire viruses. The review shows factors that have contributed to this progress - from improved models to machine-learning-based analysis and scale-bridging methods.
Coarse grained simulation of the aggregation and structure control of polyethylene nanocrystals
Polyethylene (PE) telechelics with carboxylate functional groups at both ends have been shown to assemble into hexagonal nanocrystal platelets with a height defined by their chain length in basic CsOH-solution. In this coarse grained (CG) simulation study we show how properties of the functional groups alter the aggregation and crystallization behavior of those telechelics. Systematic variation of the parameters of the CG model showed that important factors which control nanoparticle stability and structure are the PE chain length and the hydrophilicity and the steric demand of the head groups. To characterize the aggregation process we analyzed the number and size of the obtained aggregates as well as intramolecular order and intermolecular alignment of the polymer chains. By comparison of CG and atomistic simulation data, it could be shown that atomistic simulations representing different chemical systems can be emulated with specific, different CG parameter sets. Thus, the results from the (generic) CG simulation models can be used to explain the effect of different head groups and different counterions on the aggregation of PE telechelics and the order of the obtained nanocrystals.