This is rather time consuming, especially if large Gaussian basis sets were used to form molecular orbitals, but should give the best representation of the electrostatic potential. First, it can calculate the true electrostatic potential based on molecular orbital data. MOLDEN offers three ways to evaluate the electrostatic potential. MOLDEN is able to calculate electron density surfaces and electrostatic potential surfaces based on the information in the output files of Gaussian or Firefly (PC GAMESS) calculations. Many molecular visualization programs allows display of electrostatic potential maps based on quantum chemical calculations. The latter are more widely used because they retain the sense of underlying chemical structure better than isocontour plots. Electrostatic potential surfaces can be either displayed as isocontour surfaces or mapped onto the molecular electron density. These surfaces can be used to compare different inhibitors with substrates or transition states of the reaction. Electrostatic Potential SurfacesĮlectrostatic potential surfaces are valuable in computer-aided drug design because they help in optimization of electrostatic interactions between the protein and the ligand. For larger molecules, such as proteins, Connolly surfaces and solvent-accessible surfaces can be calculated rapidly based on empirical van der Waals radii of atoms. Such calculations necessitate a quantum chemical approach and are possible with most drug-like organic molecules. One way to determine molecular shape is to calculate the electron density, and display the region where the electron density is larger than some cut-off value as a three-dimensional surface. The electron density depends on the atomic composition and the chemical connectivity of atoms in the molecule. In typical molecules, the increase is so rapid that one molecule cannot penetrate into a region just about half an angstrom beyond the point of minimum interaction. Instead, the electron density falls off roughly exponentially with the distance from the nucleus, and the repulsive energy grows roughly exponentially as the distance between two nuclei decreases. However, the quantum mechanics is a probabilistic theory and there is no sharp boundary between a region that the second molecule is prohibited from entering, and the rest of the space. The shape of a molecule is determined by the electron density of the molecule because the Pauli exclusion principle prohibits the the intrusion of a second molecule into the region where a pair of electrons from the first molecule already resides. In order to rationally design molecules with a good shape complementarity, the question of what determines a shape of the molecular surface must be considered. In summary, tight binding is achieved when the shape and the charge distribution of the receptor cavity is optimally matched by the shape and the charge distribution of the ligand molecule. Few of the forces, such as the Coulombic attraction between unlike charges are rather long range, but in the aqueous solution water between interacting charges strongly attenuates the interaction. Many of the forces that drive molecular recognition are short-range strong interactions is achieved only if the molecular surfaces of interacting moieties can be close to each other. the London dispersion attraction between any two electron clouds.charge transfer between electron-rich and electron-poor molecules.induced polarization of delocalized electrons by nearby charges and dipoles.attraction between positive "crowns" of halogen atoms and lone pairs.attraction between cations and π electron clouds of aromatic residues.attraction between the opposite ends of dipoles.Molecular recognition involves specific interaction between molecules that lead to the formation of thermodynamically stable, relatively long-lived complexes. Molecular Electron Density Surface Shape and Charge Complementarity in Molecular Recognition
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