Exploring cavity dynamics in biomolecular systems

Background The internal cavities of proteins are dynamic structures and their dynamics may be associated with conformational changes which are required for the functioning of the protein. In order to study the dynamics of these internal protein cavities, appropriate tools are required that allow rapid identification of the cavities as well as assessment of their time-dependent structures. Results In this paper, we present such a tool and give results that illustrate the applicability for the analysis of molecular dynamics trajectories. Our algorithm consists of a pre-processing step where the structure of the cavity is computed from the Voronoi diagram of the van der Waals spheres based on coordinate sets from the molecular dynamics trajectory. The pre-processing step is followed by an interactive stage, where the user can compute, select and visualize the dynamic cavities. Importantly, the tool we discuss here allows the user to analyze the time-dependent changes of the components of the cavity structure. An overview of the cavity dynamics is derived by rendering the dynamic cavities in a single image that gives the cavity surface colored according to its time-dependent dynamics. Conclusion The Voronoi-based approach used here enables the user to perform accurate computations of the geometry of the internal cavities in biomolecules. For the first time, it is possible to compute dynamic molecular paths that have a user-defined minimum constriction size. To illustrate the usefulness of the tool for understanding protein dynamics, we probe the dynamic structure of internal cavities in the bacteriorhodopsin proton pump

First PACS‐integrated artificial intelligence‐based software tool for rapid and fully automatic analysis of body composition from CT in clinical routine

Background: To externally evaluate the first picture archiving communications system (PACS)-integrated artificial intelligence (AI)-based workflow, trained to automatically detect a predefined computed tomography (CT) slice at the third lumbar vertebra (L3) and automatically perform complete image segmentation for analysis of CT body composition and to compare its performance with that of an established semi-automatic segmentation tool regarding speed and accuracy of tissue area calculation. Methods: For fully automatic analysis of body composition with L3 recognition, U-Nets were trained (Visage) and compared with a conventional image segmentation software (TomoVision). Tissue was differentiated into psoas muscle, skeletal muscle, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Mid-L3 level images from randomly selected DICOM slice files of 20 CT scans acquired with various imaging protocols were segmented with both methods. Results: Success rate of AI-based L3 recognition was 100%. Compared with semi-automatic, fully automatic AI-based image segmentation yielded relative differences of 0.22% and 0.16% for skeletal muscle, 0.47% and 0.49% for psoas muscle, 0.42% and 0.42% for VAT and 0.18% and 0.18% for SAT. AI-based fully automatic segmentation was significantly faster than semi-automatic segmentation (3 ± 0 s vs. 170 ± 40 s, P < 0.001, for User 1 and 152 ± 40 s, P < 0.001, for User 2). Conclusion: Rapid fully automatic AI-based, PACS-integrated assessment of body composition yields identical results without transfer of critical patient data. Additional metabolic information can be inserted into the patient’s image report and offered to the referring clinicians

Visuelle Analyse atomarer Strukturen basierend auf dem Modell harter Kugeln

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.Die Visualisierung und Analyse atomarer Strukturen ist essenziell für das Verständnis des Aufbaus und der Funktionsweise von Molekülen. Es gibt vielfältige Anwendungsgebiete, angefangen von Grundlagenforschungen in der Biophysik und den Materialwissenschaften bis hin zur Medikamentenentwicklung in der Pharmazie. Das Modell harter Kugeln, auch Kalottenmodell genannt, ist dabei das am häufigsten verwendete Molekülmodell. Obwohl es ein sehr vereinfachtes Modell ist, ermöglicht es die geometrische Betrachtung wichtiger physikalischer Eigenschaften und erlaubt zudem, große Daten mit Tausenden bis hin zu Millionen von Atomen darzustellen und zu analysieren. Neben einer adequaten und performanten Visualisierung der Daten spielt vor allem die Extraktion von Strukturen eine große Rolle. Bei der Untersuchung von Biomolekülen, wie Proteinen, ist besonders die Analyse und Dynamik der Kavitäten von großem Interesse. In den Kavitäten können Substrate binden, die damit die Funktionsweise eines Proteins ändern, oder sie können durch die Dynamik der Kavitäten durch Membranen transportiert werden. Sowohl für die Visualisierung als auch für die Analyse der Kavitäten werden in dieser Dissertation die folgenden Beiträge geleistet: 1\. Zum einen wird die Darstellung glatter Oberflächen, die sich für die Analyse von Kavitäten eignen, beschleunigt und visuell verbessert, wodurch sie auf dynamische Proteine angewendet werden können. Zum anderen werden Methoden vorgestellt, die erstmals erlauben große statische biologische Strukturen und anorganische Materialien bis auf atomare Auflösung interaktiv darzustellen. 2\. Für die Extraktion von Kavitäten wird ein Voronoi-basiertes Verfahren mit einer hohen geometrischen Genaugkeit bei einer vergleichsweise hohen Geschwindigkeit vorgestellt. Dazu werden neue Methoden präsentiert, welche die Kavitäten innerhalb der molekularen Struktur darstellen und hervorheben. Des Weiteren werden die Methoden für dynamische Daten erweitert, um Kavitäten über die Zeit verfolgen und topologische Veränderungen visualisieren zu können. 3\. Um die Genauigkeit der oben genannten Verfahren weiter voranzutreiben, wird eine neue Moleküloberfläche vorgestellt, welche die erreichbaren Regionen eines Substrates zeigt. Dabei wird erstmals die Struktur und Dynamik des Substrates in Form des Kalottenmodells berücksichtigt. Neben der Definition der Oberfläche wird ein effizienter Algorithmus für dessen Berechnung präsentiert, der es zudem erlaubt Kavitäten zu extrahieren. Die vorgestellten Algorithmen werde an verschiedenen molekularen Daten demonstriert. Die Daten sind das Ergebnis physikalischer und biologischer Experimente oder stammen aus molekularen Simulationen

Visual Analysis of Atomic Structures Based on the Hard-Sphere Model

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

Interactive Rendering of Materials and Biological Structures on Atomic and Nanoscopic Scale

The properties of both inorganic and organic materials and the function of biological structures can often only be understood by analyzing them simultaneously on atomic and nanoscopic, if not mesoscopic, scale. Here, the problem arises to render millions to billions of atoms. We propose a method by which it is possible to interactively visualize atomic data, bridging five orders of magnitude in length scale. For this, we propose a simple yet efficient GPU rendering method that enables interactive visualization of biological structures consisting of up to several billions of atoms. To be able to load all atomic data onto the GPU, we exploit the fact that biological structures often consist of recurring molecular substructures. We also exploit that these objects typically are rendered opaquely, so that only a fraction of the atoms is visible. The method is demonstrated on both biological structures as well as atom probe tomography data of an inorganic specimen. We conclude with a discussion about when during ascension from atomic to mesoscopic scale level-of-detail representations become necessary.Computer Graphics Forum3

Atomic Accessibility Radii for Molecular Dynamics Analysis

In molecular structure analysis and visualization, the molecule’s atoms are often modeled as hard spheres parametrized by their positions and radii. While the atom positions result from experiments or molecular simulations, for the radii typically values are taken from literature. Most often, van der Waals (vdW) radii are used, for which diverse values exist. As a consequence, different visualization and analysis tools use different atomic radii, and the analyses are less objective than often believed. Furthermore, for the geometric accessibility analysis of molecular structures, vdW radii are not well suited. The reason is that during the molecular dynamics simulation, depending on the force field and the kinetic energy in the system, non-bonded atoms can come so close to each other that their vdW spheres intersect. In this paper, we introduce a new kind of atomic radius, called atomic accessibility radius’, that better characterizes the accessibility of an atom in a given molecular trajectory. The new radii reflect the movement possibilities of atoms in the simulated physical system. They are computed by solving a linear program that maximizes the radii of the atoms under the constraint that non-bonded spheres do not intersect in the considered molecular trajectory. Using this data-driven approach, the actual accessibility of atoms can be visualized more precisely

Atomic Accessibility Radii for Molecular Dynamics Analysis

In molecular structure analysis and visualization, the molecule’s atoms are often modeled as hard spheres parametrized by their positions and radii. While the atom positions result from experiments or molecular simulations, for the radii typically values are taken from literature. Most often, van der Waals (vdW) radii are used, for which diverse values exist. As a consequence, different visualization and analysis tools use different atomic radii, and the analyses are less objective than often believed. Furthermore, for the geometric accessibility analysis of molecular structures, vdW radii are not well suited. The reason is that during the molecular dynamics simulation, depending on the force field and the kinetic energy in the system, non-bonded atoms can come so close to each other that their vdW spheres intersect. In this paper, we introduce a new kind of atomic radius, called atomic accessibility radius’, that better characterizes the accessibility of an atom in a given molecular trajectory. The new radii reflect the movement possibilities of atoms in the simulated physical system. They are computed by solving a linear program that maximizes the radii of the atoms under the constraint that non-bonded spheres do not intersect in the considered molecular trajectory. Using this data-driven approach, the actual accessibility of atoms can be visualized more precisely