Multi-Scale Surface Descriptors

Abstract-We present an approach to represent DNA nanostructures in varying forms of semantic abstraction, describe ways to smoothly transition between them, and thus create a continuous multiscale visualization and interaction space for applications in DNA nanotechnology. This new way of observing, interacting with, and creating DNA nanostructures enables domain experts to approach their work in any of the semantic abstraction levels, supporting both low-level manipulations and high-level visualization and modifications. Our approach allows them to deal with the increasingly complex DNA objects that they are designing, to improve their features, and to add novel functions in a way that no existing single-scale approach offers today. For this purpose we collaborated with DNA nanotechnology experts to design a set of ten semantic scales. These scales take the DNA's chemical and structural behavior into account and depict it from atoms to the targeted architecture with increasing levels of abstraction. To create coherence between the discrete scales, we seamlessly transition between them in a well-defined manner. We use special encodings to allow experts to estimate the nanoscale object's stability. We also add scale-adaptive interactions that facilitate the intuitive modification of complex structures at multiple scales. We demonstrate the applicability of our approach on an experimental use case. Moreover, feedback from our collaborating domain experts confirmed an increased time efficiency and certainty for analysis and modification tasks on complex DNA structures. Our method thus offers exciting new opportunities with promising applications in medicine and biotechnology.

Section: Related Workmentioning

confidence: 99%

Multiscale Visualization and Scale-Adaptive Modification of DNA Nanostructures

Miao

Llano

Sorger

et al. 2018

“…To realize a more intuitive communication, also modified shading algorithms are applied when visualizing complex molecular models. One of the most popular techniques used in this context is ambient occlusion [51,28,15,25,14,20], but also contour lines [47,29] or hatching [7,31] have been applied. 3D molecular interaction visualization.…”

Section: Related Workmentioning

confidence: 99%

Physics-Based Visual Characterization of Molecular Interaction Forces

Hermosilla

Estrada

Guallar

et al. 2017

Fig. 1. Successive steps during the visual analysis of the binding nature of Aspirin and the Phospholipase A2 protein. We compute and visualize all essential interaction energies represented by 2D and 3D arrows. The orientation of the depicted arrows encodes the sign of the energy, i.e., attracting vs. repelling force. The width of the arrows as well as the color of the residue's silhouettes support energy quantification. During the visual analysis, energies are computed and depicted on-the-fly to support interactive hypothesis testing (left), and residues can be filtered based on energy and distance to obtain a more focused view (middle). Additionally, a 2D visualization helps to obtain total energy values in an uncluttered manner (right).Abstract-Molecular simulations are used in many areas of biotechnology, such as drug design and enzyme engineering. Despite the development of automatic computational protocols, analysis of molecular interactions is still a major aspect where human comprehension and intuition are key to accelerate, analyze, and propose modifications to the molecule of interest. Most visualization algorithms help the users by providing an accurate depiction of the spatial arrangement: the atoms involved in inter-molecular contacts. There are few tools that provide visual information on the forces governing molecular docking. Unfortunately these tools, commonly restricted to close interaction between atoms, do not consider whole simulation paths, long-range distances and, importantly, do not provide visual cues for a quicker and intuitive comprehension of the energy functions (modeling intermolecular interactions) involved. In this paper, we propose visualizations designed to enable the characterization of interaction forces by taking into account several relevant variables such as molecule-ligand distance and the energy function, which is essential to understand binding affinities. We put emphasis on mapping molecular docking paths obtained from Molecular Dynamics or Monte Carlo simulations, and provide time-dependent visualizations for different energy components and particle resolutions: atoms, groups or residues. The presented visualizations have the potential to support domain experts in a more efficient drug or enzyme design process.

“…Lawonn et al add feature lines, and hatching to emphasize features like cavities, channels, and pockets [29]. Cipriano et al also add hatching effects by analyzing surface properties [8]. Another popular method to facilitate spatial comprehension is the inclusion of AO [17,27,45].…”

Section: Related Workmentioning

confidence: 99%

Real-Time Molecular Visualization Supporting Diffuse Interreflections and Ambient Occlusion

Skånberg

Vázquez

Guallar

et al. 2016

(a) Time step 1 (b) Time step 2 (c) Time step 3 Fig. 1. By deriving analytic expressions, we can enhance molecular visualizations and realize interreflections in real-time. The images (a-c) show three time steps of a molecular simulation investigating the interaction between a magenta-colored ligand and a receptor molecule, which receives exaggerated diffuse interreflections. Due to these interreflections it can be seen how the ligand enters the active site.Abstract-Today molecular simulations produce complex data sets capturing the interactions of molecules in detail. Due to the complexity of this time-varying data, advanced visualization techniques are required to support its visual analysis. Current molecular visualization techniques utilize ambient occlusion as a global illumination approximation to improve spatial comprehension. Besides these shadow-like effects, interreflections are also known to improve the spatial comprehension of complex geometric structures. Unfortunately, the inherent computational complexity of interreflections would forbid interactive exploration, which is mandatory in many scenarios dealing with static and time-varying data. In this paper, we introduce a novel analytic approach for capturing interreflections of molecular structures in real-time. By exploiting the knowledge of the underlying space filling representations, we are able to reduce the required parameters and can thus apply symbolic regression to obtain an analytic expression for interreflections. We show how to obtain the data required for the symbolic regression analysis, and how to exploit our analytic solution to enhance interactive molecular visualizations.