Quality meshing of implicit solvation models of biomolecular structures

Authors:
Yongjie Zhang;Guoliang Xu;Chandrajit Bajaj
Affiliations:
Computational Visualization Center, Department of Computer Sciences, Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX;State Key Laboratory of Scientific and Engineering Computing, Institute of Computational Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing, China;Computational Visualization Center, Department of Computer Sciences, Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX
Venue:
Computer Aided Geometric Design - Special issue: Applications of geometric modeling in the life sciences
Year:
2006

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Abstract

This paper describes a comprehensive approach to construct quality meshes for implicit solvation models of biomolecular structures starting from atomic resolution data in the Protein Data Bank (PDB). First, a smooth volumetric electron density map is constructed from atomic data using weighted Gaussian isotropic kernel functions and a two-level clustering technique. This enables the selection of a smooth implicit solvation surface approximation to the Lee-Richards molecular surface. Next, a modified dual contouring method is used to extract triangular meshes for the surface, and tetrahedral meshes for the volume inside or outside the molecule within a bounding sphere/box of influence. Finally, geometric flow techniques are used to improve the surface and volume mesh quality. Several examples are presented, including generated meshes for biomolecules that have been successfully used in finite element simulations involving solvation energetics and binding rate constants.