Unfolding and Interactive Exploration of Protein Tunnels and their Dynamics

Abstract

The presence of tunnels in protein structures substantially influences their reactivity with other molecules. Therefore, studying their properties and changes over time has been in the scope of biochemists for decades. In this paper we introduce a novel approach for the comparative visualization and exploration of ensembles of tunnels. Our goal is to overcome occlusion problems with traditional tunnel representations while providing users a quick way to navigate through the input dataset and to identify potentially interesting tunnels. First, we unfold the input tunnels to a 2D representation enabling to observe the mutual position of amino acids forming the tunnel surface and the amount of surface they influence. These 2D images are subsequently described by image moments commonly used in image processing. This way we are able to detect similarities and outliers in the dataset, which are visualized as clusters in a scatterplot graph. The same coloring scheme is used in the linked bar chart enabling to detect the position of the cluster members over time. These views provide a way to select a subset of potentially interesting tunnels that can be further explored in detail using the 2D unfolded view and also traditional 3D representation. The usability of our approach is demonstrated by case studies conducted by domain experts.