Several smoothed Gaussian-based descriptors used in a molecular superposition algorithm are presented. One descriptor, as detailed in a previous work (Leherte in J Comput Chem 27:1800-1816, 2006), is the full electron density approximated through the promolecular atomic shell approximation (PASA) (Amat and Carbó-Dorca in J Chem Inf Comput Sci 40:1188-1198, 2000). Herein, we additionally present a new descriptor, that is, the charge density of a molecule calculated via the Poisson equation. The Coulomb potential as approximated by Good et al. (J Chem Inf Comput Sci 32:188-191, 1992) and atombased functions such as hydrogen bond donor or acceptor properties, lipophilicity as detailed in the work of Totrov (Chem Biol Drug Des 71:15-27, 2008) were also considered. A Monte Carlo/Simulated Annealing superposition method is applied to a set of six families of drug molecules, that is, elastase inhibitors, ligands of endothiapepsins, trypsins, thermolysins, p38 MAP kinases, and rhinovirus, all of them already reported in the literature, for discussing superposition problems. The results show that the descriptor selection can be guided by the nature of the interactions expected to occur between the drug molecules and their receptor. They also emphasize the particular efficiency of the PASA descriptor for molecules characterized by significant shape properties.
Original languageEnglish
Pages (from-to)1259/1-16
Number of pages16
JournalTheoretical Chemistry Accounts: Theory, Computation, and Modeling
Issue number8
Publication statusPublished - 1 Jan 2012


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