Modeling And Feature Analysis Of Molecular Interaction Field

Proteins play an important role in life’s processes. Exploiting the relation-ship between protein structure and function is of great significance to protein-protein interaction, protein recognition and drug design. Many scientists from different research areas, e.g., biology, chemistry, computational science, mathe-matics and physics, are trying to make some progresses in this area, based on protein structure or from other viewpoints.The function of a protein depends not only on its structure, but also on all kinds of interactions among atoms. Existing molecular models are established upon atomic position and the connections among them. Considering the three dimensional nature of protein interaction distribution, these models are difficult to analyze molecular interactions and may limit the study of molecular structure-activity relationships. In this paper, we consider the protein as a whole system composed of different kind of interactions, which is called "MIF(Molecular Inter-action Field)". Based on protein MIF, we analyze the function of protein from different viewpoints. Our work includes:●We propose a novel method to model protein MIFs. The MIF is defined as a three-dimensional uniform grid surrounding a protein of known structure with its every grid point storing the interaction of a probe with the protein. The MIF of a protein is constructed by firstly partitioning the protein space into a regular3D grid and then employing an atomic probe to compute interaction energies,i.e.,electrostactic and van der Waals interactions, on every grid point using empirical energy functions with new refinements.●We develop a haptic perceptual model for investigating protein interactions. A haptic device is used to deliver the feedback of the interaction force be-tween a protein and a probe to the user. Meanwhile, the haptic scene is rendered by mapping the protein interaction potential onto protein molec-ular surface. The MIF energy distribution can be analyzed both visually and haptically to afford much richer sensational information.●We present an efficient algorithm to detect hydrophobic patches on the surface of protein tertiary structure. Our work is base on the theory that atoms attract carbons are hydrophobic. We subdivide protein molecular surface into small regions and compute a protein MIF by using a carbon atom as a probe, then we compute the average interaction energy between every region in protein surface and a carbon based on the MIF, finally we find the regions of strong interaction energy with carbon and the amino acids in the regions. The amino acids we detect form the hydrophobic patches.●We suggest a novel technique to reconstruct protein MIFs. We reconstruct the MIFs by convolving it with a seven directional box spline and evaluate the box spline via bezier form. We analysis the influence of μ to reconstruct accuracy.We apply our methods to some typical protein systems. Experiments show that, the MIFs we built can discribe the entire structure information of protein, rep-resent the molecular potential distribution and contain abundance information about protein functions. Thus, MIFs are important to discover the structure-activity relationships, especially to recognize protein active site.