Segmenting molecular surfaces

  • Authors:
  • Vijay Natarajan;Yusu Wang;Peer-Timo Bremer;Valerio Pascucci;Bernd Hamann

  • Affiliations:
  • Institute for Data Analysis and Visualization, University of California, Davis, USA;Department of Computer Science and Engineering, The Ohio State University, USA;Department of Computer Science, University of Illinois, Urbana-Champaign, USA;Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, USA;Institute for Data Analysis and Visualization, University of California, Davis, USA and Department of Computer Science, University of California, Davis, USA

  • Venue:
  • Computer Aided Geometric Design - Special issue: Applications of geometric modeling in the life sciences
  • Year:
  • 2006

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Abstract

This paper presents a new method for segmentation of molecular surfaces. Topological analysis of a scalar function defined on the surface and its associated gradient field reveals the relationship between the features of interest and critical points of the scalar function. The segmentation is obtained by associating segments with local minima/maxima. Controlled simplification of the function merges segments resulting in a hierarchical segmentation of the molecular surface. This segmentation is used to identify rigid components of protein molecules and to study the role of cavities and protrusions in protein-protein interactions.