Visualization, manipulation and force spectroscopy of cylindrical polymer brushes

The Ph.D. thesis deals with the conformational study of individual cylindrical polymer brush molecules using atomic force microscopy (AFM). Imaging combined with single molecule manipulation has been used to unravel questions concerning conformational changes, desorption behavior and mechanical properties of individual macromolecules and supramolecular structures. In the first part of the thesis (chapter 5) molecular conformations of cylindrical polymer brushes with poly-(N-isopropylacrylamide) (PNIPAM) side chains were studied in various environmental conditions. Also micelle formation of cylindrical brush-coil blockcopolymers with polyacrylic acid side chains and polystyrene coil have been visualized. In chapter 6 the mechanical properties of single cylindrical polymer brushes with (PNIPAM) side chains were investigated. Assuming that the brushes adopt equilibrium conformation on the surface, an average persistence length of lp= (29 ± 3) nm was determined by the end-to-end distance vs. contour length analysis in terms of the wormlike chain (WLC) model. Stretching experiments suggest that an exact determination of the persistence length using force extension curves is impeded by the contribution of the side chains. Modeling the stretching of the bottle brush molecule as extension of a dual spring (side chain and main chain) explains the frequently observed very low persistence length arising from a dominant contribution of the side chain elasticity at small overall contour lengths. It has been shown that it is possible to estimate the “true” persistence length of the bottle brush molecule from the intercept of a linear extrapolation of the inverse square root of the apparent persistence length vs. the inverse contour length plot. By virtue of this procedure a “true” persistence length of 140 nm for the PNIPAM brush molecules is predicted. Chapter 7 and 8 deal with the force-extension behavior of PNIPAM cylindrical brushes studied in poor solvent conditions. The behavior is shown to be qualitatively different from that in a good solvent. Force induced globule-cylinder conformational changes are monitored using “molecule specific force spectroscopy” which is a combined AFM imaging and SMFS technique. An interesting behavior of the unfolding-folding transitions of single collapsed PNIPAM brush molecules has been observed by force spectroscopy using the so called “fly-fishing” mode. A plateau force is observed upon unfolding the collapsed molecule, which is attributed to a phase transition from a collapsed brush to a stretched conformation. Chapter 9 describes the desorption behavior of single cylindrical polyelectrolyte brushes with poly-L-lysine side chains deposited on a mica surface using the “molecule specific force spectroscopy” technique to resolve statistical discrepancies usually observed in SMFS experiments. Imaging of the brushes and inferring the persistence length from a end-to-end distance vs. contour length analysis results in an average persistence length of lp = (25 ± 5) nm assuming that the chains adopt their equilibrium conformation on the surface. Stretching experiments carried out on individual poly-L-lysine brush molecules by force spectroscopy using the “fly-fishing” mode provide a persistence length in the range of 7-23 nm in reasonable accordance with the imaging results. In chapter 10 the conformational behavior of cylindrical poly-L-lysine brush-sodium dodecyl sulfate complexes was studied using AFM imaging. Surfactant induced cylinder to helix like to globule conformational transitions were observed.

Radiolabeling of defined polymer architectures with fluorine-18 and iodine-131 for ex vivo and in vivo evaluation : visualization of structure-property relationships

Nuclear medicine imaging techniques such as PET are of increasing relevance in pharmaceutical research being valuable (pre)clinical tools to non-invasively assess drug performance in vivo. Therapeutic drugs, e.g. chemotherapeutics, often suffer from a poor balance between their efficacy and toxicity. Here, polymer based drug delivery systems can modulate the pharmacokinetics of low Mw therapeutics (prolonging blood circulation time, reducing toxic side effects, increasing target site accumulation) and therefore leading to a more efficient therapy. In this regard, poly-N-(2-hydroxypropyl)-methacrylamide (HPMA) constitutes a promising biocompatible polymer. Towards the further development of these structures, non-invasive PET imaging allows insight into structure-property relationships in vivo. This performant tool can guide design optimization towards more effective drug delivery. Hence, versatile radiolabeling strategies need to be developed and establishing 18F- as well as 131I-labeling of diverse HPMA architectures forms the basis for short- as well as long-term in vivo evaluations. By means of the prosthetic group [18F]FETos, 18F-labeling of distinct HPMA polymer architectures (homopolymers, amphiphilic copolymers as well as block copolymers) was successfully accomplished enabling their systematic evaluation in tumor bearing rats. These investigations revealed pronounced differences depending on individual polymer characteristics (molecular weight, amphiphilicity due to incorporated hydrophobic laurylmethacrylate (LMA) segments, architecture) as well as on the studied tumor model. Polymers showed higher uptake for up to 4 h p.i. into Walker 256 tumors vs. AT1 tumors (correlating to a higher cellular uptake in vitro). Highest tumor concentrations were found for amphiphilic HPMA-ran-LMA copolymers in comparison to homopolymers and block copolymers. Notably, the random LMA copolymer P4* (Mw=55 kDa, 25% LMA) exhibited most promising in vivo behavior such as highest blood retention as well as tumor uptake. Further studies concentrated on the influence of PEGylation (‘stealth effect’) in terms of improving drug delivery properties of defined polymeric micelles. Here, [18F]fluoroethylation of distinct PEGylated block copolymers (0%, 1%, 5%, 7%, 11% of incorporated PEG2kDa) enabled to systematically study the impact of PEG incorporation ratio and respective architecture on the in vivo performance. Most strikingly, higher PEG content caused prolonged blood circulation as well as a linear increase in tumor uptake (Walker 256 carcinoma). Due to the structural diversity of potential polymeric carrier systems, further versatile 18F-labeling strategies are needed. Therefore, a prosthetic 18F-labeling approach based on the Cu(I)-catalyzed click reaction was established for HPMA-based polymers, providing incorporation of fluorine-18 under mild conditions and in high yields. On this basis, a preliminary µPET study of a HPMA-based polymer – radiolabeled via the prosthetic group [18F]F-PEG3-N3 – was successfully accomplished. By revealing early pharmacokinetics, 18F-labeling enables to time-efficiently assess the potential of HPMA polymers for efficient drug delivery. Yet, investigating the long-term fate is essential, especially regarding prolonged circulation properties and passive tumor accumulation (EPR effect). Therefore, radiolabeling of diverse HPMA copolymers with the longer-lived isotope iodine-131 was accomplished enabling in vivo evaluation of copolymer P4* over several days. In this study, tumor retention of 131I-P4* could be demonstrated at least over 48h with concurrent blood clearance thereby confirming promising tumor targeting properties of amphiphilic HPMA copolymer systems based on the EPR effect.

Software tools and efficient algorithms for the feature detection, feature tracking, event localization, and visualization of large sets of atmospheric data

Data sets describing the state of the earth's atmosphere are of great importance in the atmospheric sciences. Over the last decades, the quality and sheer amount of the available data increased significantly, resulting in a rising demand for new tools capable of handling and analysing these large, multidimensional sets of atmospheric data. The interdisciplinary work presented in this thesis covers the development and the application of practical software tools and efficient algorithms from the field of computer science, aiming at the goal of enabling atmospheric scientists to analyse and to gain new insights from these large data sets. For this purpose, our tools combine novel techniques with well-established methods from different areas such as scientific visualization and data segmentation. In this thesis, three practical tools are presented. Two of these tools are software systems (Insight and IWAL) for different types of processing and interactive visualization of data, the third tool is an efficient algorithm for data segmentation implemented as part of Insight.Insight is a toolkit for the interactive, three-dimensional visualization and processing of large sets of atmospheric data, originally developed as a testing environment for the novel segmentation algorithm. It provides a dynamic system for combining at runtime data from different sources, a variety of different data processing algorithms, and several visualization techniques. Its modular architecture and flexible scripting support led to additional applications of the software, from which two examples are presented: the usage of Insight as a WMS (web map service) server, and the automatic production of a sequence of images for the visualization of cyclone simulations. The core application of Insight is the provision of the novel segmentation algorithm for the efficient detection and tracking of 3D features in large sets of atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. Data segmentation usually leads to a significant reduction of the size of the considered data. This enables a practical visualization of the data, statistical analyses of the features and their events, and the manual or automatic detection of interesting situations for subsequent detailed investigation. The concepts of the novel algorithm, its technical realization, and several extensions for avoiding under- and over-segmentation are discussed. As example applications, this thesis covers the setup and the results of the segmentation of upper-tropospheric jet streams and cyclones as full 3D objects. Finally, IWAL is presented, which is a web application for providing an easy interactive access to meteorological data visualizations, primarily aimed at students. As a web application, the needs to retrieve all input data sets and to install and handle complex visualization tools on a local machine are avoided. The main challenge in the provision of customizable visualizations to large numbers of simultaneous users was to find an acceptable trade-off between the available visualization options and the performance of the application. Besides the implementational details, benchmarks and the results of a user survey are presented.

Visualization and validation of (Q)SAR models

Analyzing and modeling relationships between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects in chemical datasets is a challenging task for scientific researchers in the field of cheminformatics. Therefore, (Q)SAR model validation is essential to ensure future model predictivity on unseen compounds. Proper validation is also one of the requirements of regulatory authorities in order to approve its use in real-world scenarios as an alternative testing method. However, at the same time, the question of how to validate a (Q)SAR model is still under discussion. In this work, we empirically compare a k-fold cross-validation with external test set validation. The introduced workflow allows to apply the built and validated models to large amounts of unseen data, and to compare the performance of the different validation approaches. Our experimental results indicate that cross-validation produces (Q)SAR models with higher predictivity than external test set validation and reduces the variance of the results. Statistical validation is important to evaluate the performance of (Q)SAR models, but does not support the user in better understanding the properties of the model or the underlying correlations. We present the 3D molecular viewer CheS-Mapper (Chemical Space Mapper) that arranges compounds in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which features to employ in the process. The tool can use and calculate different kinds of features, like structural fragments as well as quantitative chemical descriptors. Comprehensive functionalities including clustering, alignment of compounds according to their 3D structure, and feature highlighting aid the chemist to better understand patterns and regularities and relate the observations to established scientific knowledge. Even though visualization tools for analyzing (Q)SAR information in small molecule datasets exist, integrated visualization methods that allows for the investigation of model validation results are still lacking. We propose visual validation, as an approach for the graphical inspection of (Q)SAR model validation results. New functionalities in CheS-Mapper 2.0 facilitate the analysis of (Q)SAR information and allow the visual validation of (Q)SAR models. The tool enables the comparison of model predictions to the actual activity in feature space. Our approach reveals if the endpoint is modeled too specific or too generic and highlights common properties of misclassified compounds. Moreover, the researcher can use CheS-Mapper to inspect how the (Q)SAR model predicts activity cliffs. The CheS-Mapper software is freely available at http://ches-mapper.org.