We present Molecular Surface Maps, a novel, view-independent, and concise representation for molecular surfaces. It transfers the well-known world map metaphor to molecular visualization. Our application maps the complex molecular surface to a simple 2D representation through a spherical intermediate, the Molecular Surface Globe. The Molecular Surface Map concisely shows arbitrary attributes of the original molecular surface, such as biochemical properties or geometrical features. This results in an intuitive overview, which allows researchers to assess all molecular surface attributes at a glance. Our representation can be used as a visual summarization of a molecule's interface with its environment. In particular, Molecular Surface Maps simplify the analysis and comparison of different data sets or points in time. Furthermore, the map representation can be used in a Space-time Cube to analyze time-dependent data from molecular simulations without the need for animation. We show the feasibility of Molecular Surface Maps for different typical analysis tasks of biomolecular data.

Abstract The comparison of molecular surface attributes is of interest for computer aided drug design and the analysis of biochemical simulations. Due to the non‐rigid nature of molecular surfaces, partial shape matching is feasible for mapping two surfaces onto each other. We present a novel technique to obtain a mapping relation between two surfaces using a deformable model approach. This relation is used for pair‐wise comparison of local surface attributes (e.g. electrostatic potential). We combine the difference value as well as the comparability as derived from the local matching quality in a 3D molecular visualization by mapping them to color. A 2D matrix shows the global dissimilarity in an overview of different data sets in an ensemble. We apply our visualizations to simulation results provided by collaborators from the field of biochemistry to evaluate the effectiveness of our results.

Abstract We present a coordinated‐view application for the analysis of molecular surface features like cavities, channels and pockets. Our tool employs object‐space ambient occlusion for the detection of such features and tracks them over time. It offers time‐dependent graphs of metrics concerning those features and allows analyzing the temporal relationship of the features, i.e. when they (dis)appear, split or merge and which features participate in each of these events. The automated analysis process is performed in real time while the user interactively explores a dynamic data set. The system supports linking and brushing to allow for a user‐guided visual analysis based on different aspects of the data. We demonstrate the effectiveness of our approach by applying it to data sets from biochemistry and report the insights that can be gained. We also evaluate the benefits of our method with respect to recent advancements in the field. The algorithmic pipeline leverages the computing power of modern GPUs, thus achieving interactive frame rates without any precomputation for fully dynamic data sets.