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Class A G-protein-coupled receptors (GPCRs) are among the most important targets for drug discovery. However, a large set of experimental structures, essential for a structure-based approach, will likely remain unavailable in the near future. Thus, there is an actual need for modeling tools to characterize satisfactorily at least the binding site of these receptors. Using experimentally solved GPCRs, we have enhanced and validated the ligand-steered homology method through cross-modeling and investigated the performance of the thus generated models in docking-based screening. The ligand-steered modeling method uses information about existing ligands to optimize the binding site by accounting for protein flexibility. We found that our method is able to generate quality models of GPCRs by using one structural template. These models perform better than templates, crude homology models, and random selection in small-scale high-throughput docking. Better quality models typically exhibit higher enrichment in docking exercises. Moreover, they were found to be reliable for selectivity prediction. Our results support the fact that the ligand-steered homology modeling method can successfully characterize pharmacologically relevant sites through a full flexible ligand-flexible receptor procedure.

Recently, we discovered and reported a series of N-alkyl isatin acylhydrazone derivatives that are potent CB2 agonists. Here, we describe a novel series of selective CB2 inverse agonists resulting from introduction of a methoxy moiety in position 6 of the isatin scaffold. These novel 6-methoxy-N-alkyl isatin acylhydrazone derivatives exhibited high CB2 functional activity and selectivity at human CB2. Compound 16 (MDA77) had high activity (EC(50) = 5.82 nM) at CB2 and no activity at CB1. Compound 15 (MDA55) (K(i) = 89.9 nM, EC(50) = 88.2 nM at CB2) inhibited the effect of compound 1 (MDA7), a selective CB2 agonist, in an animal model of neuropathic pain. The molecular modeling study presented here represents a first study of CB2 based on the structure of beta(2)-adrenergic receptor. A ligand-based homology model of the CB2 binding site was developed, and on the basis of our results, we propose a general binding mode for this class of inverse agonists with CB2.