Three-dimensional homology models of human MT(1) and MT(2) melatonin receptors were built with the aim to investigate the structure-activity relationships (SARs) of MT(2) selective antagonists. A common interaction pattern was proposed for a series of structurally different MT(2) selective antagonists, which were positioned within the binding site by docking and simulated annealing. The proposed antagonist binding mode to the MT(2) receptor is characterized by the accommodation of the out-of-plane substituents in a hydrophobic pocket, which resulted as being fundamental for the explanation of the antagonist behavior and the MT(2) receptor selectivity. Moreover, to assess the ability of the MT(2) receptor model to reproduce the SARs of MT(2) antagonists, three new derivatives of the MT(2) selective antagonist N-[1-(4-chloro-benzyl)-4-methoxy-1H-indol-2-ylmethyl]-propionamide (7) were synthesized and tested for their receptor affinity and intrinsic activity. These compounds were docked into the MT(2) receptor model and were submitted to molecular dynamics studies, providing results in qualitative agreement with the experimental data. These results confirm the importance of the out-of-plane group in receptor binding and selectivity and provide a partial validation of the proposed G protein-coupled receptor model.

On route toward a novel de novo design program, called LiGen, we developed a docking program, LiGenDock, based on pharmacophore models of binding sites, including a non-enumerative docking algorithm. In this paper, we present the functionalities of LiGenDock and its accompanying module LiGenPocket, aimed at the binding site analysis and structure-based pharmacophore definition. We also report the optimization procedure we have carried out to improve the cognate docking and virtual screening performance of LiGenDock. In particular, we applied the design of experiments (DoE) methodology to screen the set of user-adjustable parameters to identify those having the largest influence on the accuracy of the results (which ensure the best performance in pose prediction and in virtual screening approaches) and then to choose their optimal values. The results are also compared with those obtained by two popular docking programs, namely, Glide and AutoDock for pose prediction, and Glide and DOCK6 for Virtual Screening.

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A novel series of melatonin receptor ligands was discovered by opening the cyclic scaffolds of known classes of high affinity melatonin receptor antagonists, while retaining the pharmacophore elements postulated by previously described 3D-QSAR and receptor models. Compounds belonging to the classes of 2,3- and [3,3-diphenylprop(en)yl]alkanamides and of o- or [(m-benzyl)phenyl]ethyl-alkanamides were synthesized and tested on MT(1) and MT(2) receptors. The class of 3,3-diphenyl-propenyl-alkanamides was the most interesting one, with compounds having MT(2) receptor affinity similar to that of MLT, remarkable MT(2) selectivity, and partial agonist or antagonist behavior. In particular, the (E)-m-methoxy cyclobutanecarboxamido derivative 18f and the di-(m-methoxy) acetamido one, 18g, have sub-nM affinity for the MT(2) subtype, with more than 100-fold selectivity over MT(1), 18f being an antagonist and 18g a partial agonist on GTPgammaS test. Docking of 18g into a previously developed MT(2) receptor model showed a binding scheme consistent with that of other antagonists. The MT(2) expected binding affinities of the new compounds were calculated by a previously developed 3D-QSAR CoMFA model, giving satisfactory predictions.