The Feature Analysis Of Molecular Field Based On Level Set Method

In this paper, we exploit a Level Set method to extract and analyze the feature of macromolecular field. For the 3D volume data of the field, we propose a novel variational formulation for geometric active contour, which is composed of an external energy to drive the active contours' motion, and an internal energy which penalizes the Level Set function adaptively to avoid periodically re-initializing. We adjust the parameters of each component and investigate their influence in the whole process. According to the comparison with the traditional frameworks, our approach is shown to be more accurate and efficient on the feature extraction.Based on the Level Set method constructed in the first part, we give a further analysis for the static and dynamic molecular field data. For the static molecular field, we choose the region where the energy has the quantum leap and analyze the molecular field. Then, we construct the volume feature function to extract the topological region and get the energy distribution of the whole molecular field. For the dynamic molecular field, we consider the same protein in the different states, like observing the process in changing the conformation and forming the middle tunnel. At the mean time, we calculate the multi-attributes of these states and try to find the crucial time during the movement of the molecular. According to the surface and volume rendering techniques, we reveal the significant feature of the macromolecular field.Preliminary results show that, we successfully find the escape route of water molecules hidden in the HIV-1 protease, the internal cavity of the DPS protein for the iron atom's entry and deposition and biological activity of HIV-1 protease when processing SMD simulation in the aqueous solution. Both of these results are in accordance with the experimental results given by chemists and biologists. Biologists believe that these results may be useful to study the hydrophilic and hydrophobic of HIV-1 protease in the future, and these active cites can be considered as the most important regions in the protein-protein interaction and protein-ligand interaction.