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Stefan Bruckner

Publications and source records attributed to Stefan Bruckner.

3 recordsLinked to original sources

Comparative models of GABAA receptor extracellular and transmembrane domains: important insights in pharmacology and function.

Comparative models of the extracellular and transmembrane domains of GABAA receptors in the agonist-free state were generated based on the recently published structures of the nicotinic acetylcholine receptor. The models were validated by computational methods, and their reliability was estimated by analyzing conserved and variable elements of the cys-loop receptor topology. In addition, the methodological limits in the interpretation of such anion channel receptor models are discussed. Alignment ambiguities in the helical domain were resolved for helix 3 by placing two gaps into the linker connecting helices 2 and 3. The resulting models were shown to be consistent with a wide range of pharmacological and mutagenesis data from GABAA and glycine receptors. The loose packing of the models results in a large amount of solvent-accessible space and offers a natural explanation for the rich pharmacology and the great flexibility of these receptors that are known to exist in numerous drug-induced conformational states. Putative drug binding pockets found within and between subunits are described, and amino acid residues important for the action and subtype selectivity of volatile and intravenous anesthetics, barbiturates, and furosemide are shown to be part of these pockets. The entire helical domain, however, seems to be crucial not only for binding of drugs but also for transduction of binding to gating or of allosteric modulation. These models can now be used to design new experiments for clarification of pharmacological and structural questions as well as for investigating and visualizing drug induced conformational changes.

Amino Acid Sequence↗

Exploded views for volume data.

Exploded views are an illustration technique where an object is partitioned into several segments. These segments are displaced to reveal otherwise hidden detail. In this paper we apply the concept of exploded views to volumetric data in order to solve the general problem of occlusion. In many cases an object of interest is occluded by other structures. While transparency or cutaways can be used to reveal a focus object, these techniques remove parts of the context information. Exploded views, on the other hand, do not suffer from this drawback. Our approach employs a force-based model: the volume is divided into a part configuration controlled by a number of forces and constraints. The focus object exerts an explosion force causing the parts to arrange according to the given constraints. We show that this novel and flexible approach allows for a wide variety of explosion-based visualizations including view-dependent explosions. Furthermore, we present a high-quality GPU-based volume ray casting algorithm for exploded views which allows rendering and interaction at several frames per second.

Algorithms↗

Illustrative context-preserving exploration of volume data.

In volume rendering, it is very difficult to simultaneously visualize interior and exterior structures while preserving clear shape cues. Highly transparent transfer functions produce cluttered images with many overlapping structures, while clipping techniques completely remove possibly important context information. In this paper, we present a new model for volume rendering, inspired by from illustration. It provides a means of interactively inspecting the interior of a volumetric data set in a feature-driven way which retains context information. The context-preserving volume rendering model uses a function of shading intensity, gradient magnitude, distance to the eye point, and previously accumulated opacity to selectively reduce the opacity in less important data regions. It is controlled by two user-specified parameters. This new method represents an alternative to conventional clipping techniques, sharing their easy and intuitive user control, but does not suffer from the drawback of missing context information.

Algorithms↗