Amesergide

A set of 31 diversified 5-HT7 receptor antagonists was automatically docked to a conformational ensemble of rhodopsin-based 5-HT7R models (flexible docking). It was found that ergolines, aporphines, and tricyclic psychotropic agents were always docked in a pocket formed by TMHs 4-6, and besides the main ionic bond with Asp3.32, they had specific interactions with Phe6.52, Phe6.51, Trp6.48, and Ser5.42. The arylpiperidine, arylpiperazine, or beta-carboline fragment of the complex ligands occupied the same pocket, whereas the terminal amide/imide part of those compounds reached the second cavity formed by TMHs 7-3 and interacted with Phe3.28, Arg7.36, and Tyr7.43. A similar orientation of selective antagonists of the group of arylsulfonamidoalkylamines was observed, that is, the sulfonamide part was located in the second pocket. Coherent docking results allowed the generation of two receptor-based pharmacophores: first containing features necessary for high 5-HT7R affinity and the other defining selectivity for this receptor subtype. The latter model indicated the importance of specific interactions with the residues of the TMHs 7-3 pocket (especially nonconserved Arg7.36) for selectivity over other monoamine GPCRs.

In today's drug discovery process, the very early consideration of ADME properties is aimed at a reduction of drug candidate drop out rate in later development stages. Apart from in vitro testing, in silico methods are evaluated as complementary screening tools for compounds with unfavorable ADME attributes. Especially members of the cytochrome P450 (P450) enzyme superfamily-- e.g. P450 1A2, P450 2C9, P450 2C19, P450 2D6, and P450 3A4-- contribute to xenobiotic metabolism, and compound interaction with one of these enzymes is therefore critically evaluated. Pharmacophore models are widely used to identify common features amongst ligands for any target. In this study, both structure-based and ligand-based models for prominent drug-metabolizing members of the P450 family were generated employing the software packages LigandScout and Catalyst. Essential chemical ligand features for substrate and inhibitor activity for all five P450 enzymes investigated were determined and analyzed. Finally, a collection of 11 pharmacophores for substrates and inhibitors was evaluated as an in silico P450 profiling tool that could be used for early ADME estimation of new chemical entities.