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In this report we review and structure the branch of molecular visualization that is concerned with the visual analysis of cavities in macromolecular protein structures. First the necessary background, the domain terminology, and the goals of analytical reasoning are introduced. Based on a comprehensive collection of relevant research works, we present a novel classification for cavity detection approaches and structure them into four distinct classes: grid-based, Voronoi-based, surface-based, and probe-based methods. The subclasses are then formed by their combinations. We match these approaches with corresponding visualization technologies starting with direct 3D visualization, followed with non-spatial visualization techniques that for example abstract the interactions between structures into a relational graph, straighten the cavity of interest to see its profile in one view, or aggregate the time sequence into a single contour plot. We also discuss the current state of methods for the visual analysis of cavities in dynamic data such as molecular dynamics simulations. Finally, we give an overview of the most common tools that are actively developed and used in the structural biology and biochemistry research. Our report is concluded by an outlook on future challenges in the field.
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.
When physical unfolding/unrolling of papyri is not possible or too dangerous for preserving the precious object, tomographic approaches may be the ap- propriate alternative. Requirements are the resolution and the contrast to distinguish writing and substrate. The steps to be performed are the following: (1) Select the object of interest (archaeological arguments, cultural back- ground of the object, etc.). (2) Find the proper physical procedure, especially with respect to contrast, take the tomographic data, e.g. by absorption x-ray tomography. (3) Apply mathematical unfolding transformations to the tomographic data, in order to obtain a 2d-planar reconstruction of text.
Structural properties of molecules are of primary concern in many fields. This report provides a comprehensive overview on techniques that have been developed in the fields of molecular graphics and visualization with a focus on applications in structural biology. The field heavily relies on computerized geometric and visual representations of three-dimensional, complex, large and time-varying molecular structures. The report presents a taxonomy that demonstrates which areas of molecular visualization have already been extensively investigated and where the field is currently heading. It discusses visualizations for molecular structures, strategies for efficient display regarding image quality and frame rate, covers different aspects of level of detail and reviews visualizations illustrating the dynamic aspects of molecular simulation data. The survey concludes with an outlook on promising and important research topics to foster further success in the development of tools that help to reveal molecular secrets.
In this report we review and structure the branch of molecular visualization that is concerned with the visual analysis of cavities in macromolecular protein structures. First the necessary background, the domain terminology, and the goals of analytical reasoning are introduced. Based on a comprehensive collection of relevant research works, we present a novel classification for cavity detection approaches and structure them into four distinct classes: grid-based, Voronoi-based, surface-based, and probe-based methods. The subclasses are then formed by their combinations. We match these approaches with corresponding visualization technologies starting with direct 3D visualization, followed with non-spatial visualization techniques that for example abstract the interactions between structures into a relational graph, straighten the cavity of interest to see its profile in one view, or aggregate the time sequence into a single contour plot. We also discuss the current state of methods for the visual analysis of cavities in dynamic data such as molecular dynamics simulations. Finally, we give an overview of the most common tools that are actively developed and used in the structural biology and biochemistry research. Our report is concluded by an outlook on future challenges in the field.