Parallel Computation of Voxelized Macromolecular Surfaces by Spatial Slicing

We propose an algorithm for the computation of discrete macromolecular surface representations. By employing compact data-structures and implementing a spatial slicing protocol, the procedure can calculate the three main molecular surfaces, namely van der Waals, Solvent-Accessible and Solvent-Excluded, at high resolutions in parallel. Fast surface generation is achieved by adopting an approximate Euclidean Distance Transform algorithm in the Solvent Excluded surface computation step. By exploiting the geometrical relationship between the Solvent Excluded and the Solvent Accessible surfaces, we show that the distance map values need to be calculated only for a small subset of the overall voxels representing the macromolecule. This is achieved by employing a region-growing strategy based on a data-structure called Hierarchical Queue.