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.

中文翻译：

---

生物分子结构隐式求解模型的质量网格划分。

本文描述了一种从蛋白质数据库 (PDB) 中的原子分辨率数据开始为生物分子结构的隐式溶剂化模型构建质量网格的综合方法。首先，使用加权高斯各向同性核函数和两级聚类技术从原子数据构建平滑的体积电子密度图。这使得可以选择近似于 Lee-Richards 分子表面的平滑隐式溶剂化表面。接下来，使用改进的双重轮廓法提取表面的三角形网格，以及边界球/影响框内分子内部或外部的体积的四面体网格。最后，几何流动技术用于提高表面和体积网格质量。给出了几个例子，