Abstract

The quality of chiral environment (i.e. catalytic pocket) is directly related to the performance of chiral catalysts. The existing methods need super computing power and time, i.e., it is difficult to quickly judge the interaction between chiral catalysts and substrates for accurately evaluating the effects of chiral catalytic pockets. In this paper, for the 3D isosurface point clouds of molecular electrostatic potential, by using computer simulations, we propose a robust method to detect interacted points, and then accurately have the corresponding interacted volumes. First, by using the existing marching cubes algorithm, we construct the 3D models with triangular surface for isosurface point clouds of molecular electrostatic potentials. Second, by using our improved hierarchical bounding boxes algorithm, we significantly filter out most redundant non-collision points. Third, by using the normal vectors of the remaining points and related triangles, we robustly determine the interacted points to construct interacted sets. And finally, by combining the classical slicing with our multi-contour segmenting, we accurately calculate the interacted volumes. Over three groups of the point clouds of the chemical molecules, experimental results show that our method effectively removes the non-interacted points at average rates of 71.65%, 77.76%, and 71.82%, and calculates the interacted volumes with the average relative errors of 1.7%, 1.6%, and 1.9%, respectively.

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