Real-time Visualization and Exploration of Protein Empty Space with Varying Parameters
| Authors | |
|---|---|
| Year of publication | 2013 |
| Type | Article in Periodical |
| Magazine / Source | International Journal on Advances in Life Sciences |
| MU Faculty or unit | |
| Citation | |
| Field | Informatics |
| Keywords | protein; empty space; void; visualization; real-time; cavity; volume; Voronoi diagram; Delaunay triangulation |
| Description | Long-term research in the area of protein analysis proved the importance of an empty space situated inside these macromolecular structures. This empty space influences the protein function, characteristics or reactivity. Many algorithms enabling computation of these empty spaces (or voids) have been published and their results were evaluated by protein engineers to confirm their chemical relevance. However, not all detected voids inside protein are of the same importance. Thus, the examination and assessment of all voids must follow to reveal the important ones. In this phase the visual representation of voids is very valuable and substantially decreases the time spent in this evaluation phase. In this paper we present an extension of the algorithm for the visualization and further evaluation of protein voids in real-time. The user-driven approach enables to compute and display empty space that satisfies the input parameters instantly. The values of these parameters can be changed by the user anytime and the changes are immediately displayed and prepared for further exploration. Our improvements involve an exclusion of selected atom or group of atoms (ligands, ions) from the computation, which can change the size and shape of the detected void. Another improvement is related to the detection of the binding site which is usually located in one of the largest voids. So the algorithm suggests and visually separates (by different coloring) the largest void of given area. Several improvements were also made in the field of real-time exploration – currently the interaction on large structures is fluent. In consequence, the current version of the algorithm provides the biochemists with very adjustable and precise algorithm for detection of inner voids in a user-defined region of protein structures. |
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