Computational Visualization Center (CVC)

Institute for Computational Engineering and Sciences & Dept. of Computer Sciences

The University of Texas at Austin

Institute of Computational Mathematics and Scientific/Engineering Computing

Academy of Mathematics and System Sciences

Chinese Academy of Sciences, China

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, multi-scale volumetric synthetic electron density maps are constructed from parsed atomic location data of biomolecules in the PDB, using Gaussian isotropic kernels. An appropriate parameter selection is made for constructing an error bounded implicit solvation surface approximation to the Lee-Richards molecular surface. Next, a modified dual contouring method is used to extract triangular meshes for the molecular surface, and tetrahedral meshes for the volume inside or outside the molecule within a bounding sphere/box of influence. Finally, geometric flows are used to improve the mesh quality. Some of our generated meshes have been successfully used in finite element simulations.