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Visualization and Analysis of atomic compositions is essential to understand
the structure and functionality of molecules. There exist versatile areas of applications, from fundamental researches in biophysics and materials science to
drug development in pharmaceutics. For most applications, the hard-sphere
model is the most often used molecular model. Although the model is a quite
simple approximation of reality, it enables investigating important physical
properties in a purely geometrical manner. Furthermore, large data sets with
thousands up to millions of atoms can be visualized and analyzed. In addition to an adequate and efficient visualization of the data, the extraction of
important structures plays a major role. For the investigation of biomolecules,
such as proteins, especially the analysis of cavities and their dynamics is of
high interest. Substrates can bind in cavities, thereby inducing changes in
the function of the protein. Another example is the transport of substrates
through membrane proteins by the dynamics of the cavities. For both, the
visualization as well as the analysis of cavities, the following contributions
will be presented in this thesis:
1. The rendering of smooth molecular surfaces for the analysis of cavities
is accelerated and visually improved, which allows showing dynamic
proteins. On the other hand, techniques are proposed to interactively
render large static biological structures and inorganic materials up to
atomic resolution for the first time.
2. A Voronoi-based method is presented to extract molecular cavities. The
procedure comes with a high geometrical accuracy by a comparatively
fast computation time. Additionally, new methods are presented to visualize and highlight the cavities within the molecular structure. In a
further step, the techniques are extended for dynamic molecular data to
trace cavities over time and visualize topological changes.
3. To further improve the accuracy of the approaches mentioned above, a
new molecular surface model is presented that shows the accessibility
of a substrate. For the first time, the structure and dynamics of the substrate as hard-sphere model is considered for the accessibility computation. In addition to the definition of the surface, an efficient algorithm
for its computation is proposed, which additionally allows extracting
cavities.
The presented algorithms are demonstrated on different molecular data
sets. The data sets are either the result of physical or biological experiments
or molecular dynamics simulations.