Implicit surfaces for interactive graph based cavity analysis of molecular simulations

Julius Parulek*, Cagatay Turkay, Nathalie Reuter, Ivan Viola

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Scopus citations

Abstract

Molecular surfaces provide a suitable way to analyze and to study the evolution and interaction of molecules. The analysis is often concerned with visual identification of binding sites of ligands to a host macromolecule. We present a novel technique that is based on implicit representation, which extracts all potential binding sites and allows an advanced 3D visualization of these sites in the context of the molecule. We utilize implicit function sampling strategy to obtain potential cavity samples and graph algorithms to extract arbitrary cavity components defined by simple graphs. Moreover, we propose how to interactively visualize these graphs in the context of the molecular surface. We also introduce a system of linked views depicting various graph parameters that are used to perform a more elaborative study on created graphs.

Original languageEnglish (US)
Title of host publicationIEEE Symposium on Biological Data Visualization 2012, BioVis 2012 - Proceedings
Pages115-122
Number of pages8
DOIs
StatePublished - 2012
Externally publishedYes
Event2nd IEEE Symposium on Biological Data Visualization, BioVis 2012 - Seattle, WA, United States
Duration: Oct 14 2012Oct 19 2012

Publication series

NameIEEE Symposium on Biological Data Visualization 2012, BioVis 2012 - Proceedings

Conference

Conference2nd IEEE Symposium on Biological Data Visualization, BioVis 2012
Country/TerritoryUnited States
CitySeattle, WA
Period10/14/1210/19/12

Keywords

  • I.3.4 [Computer Graphics]: Computational Geometry and Object Modeling - Boundary representations, Curve, surface, solid and object representations
  • J.3 [Computer Applications]: Life and Medical Sciences - Biology and Genetics

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Bioengineering

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