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To probe the selective mechanism of agonists binding to three opioid receptor subtypes, ligand-based and receptor-based methods were implemented together and subtype characteristics of opioid agonists were clearly described. Three pharmacophore models of opioid agonists were generated by the Catalyst/HypoGen program. The best pharmacophore models for μ, δ and κ agonists contained four, five and five features, respectively. Meanwhile, the three-dimensional structures of three receptor subtypes were modeled on the basis of the crystal structure of β2-adrenergic receptor, and molecular docking was conducted further. According to these pharmacophore models and docking results, the similarities and differences among agonists of three subtypes were identified. μ or δ agonists, for example, could form one hydrogen bond separately with Tyr129 and Tyr150 at TMIII, whereas κ ones formed a π-π interaction in that place. These findings may be crucial for the development of novel selective analgesic drugs.

Two chemical function-based pharmacophore models of selective kappa-opioid receptor agonists were generated by using two different programs: Catalyst/HypoGen and Phase. The best output hypothesis (Hypo1) of HypoGen consisted of five features: one hydrogen-bond acceptor (HA), three hydrophobic points (HY), and one positive ionizable function (PI). The highest scoring model (Hypo2) produced by Phase comprised four features: one acceptor (A), one positive ionizable function (P), and two aromatic ring features (R). These two models (Hypo1 and Hypo2) were then validated by test set prediction and enrichment factors. They were shown to be able to identify highly potent kappa-agonists within a certain range, and satisfactory enrichments were achieved. The features of these two pharmacophore models were similar and consistent with experiment data. The models produced here were also generally in accord with other reported models. Therefore, our pharmacophore models were considered as valuable tools for 3D virtual screening, and could be useful for designing novel kappa-agonists.

Structure-based 3D-QSAR studies were performed on 20 thiazoles against their binding affinities to the 5-HT(3) receptor with comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The thiazoles were initially docked into the binding pocket of a human 5-HT(3A) receptor homology model, constructed on the basis of the crystal structure of the snail acetylcholine binding protein (AChBP), using the GOLD program. The docked conformations were then extracted and used to build the 3D-QSAR models, with cross-validated r2omega values 0.785 and 0.744 for CoMFA and CoMSIA, respectively. An additional five molecules were used to validate the models further, giving satisfactory predictive r2 values of 0.582 and 0.804 for CoMFA and CoMSIA, respectively. The results would be helpful for the discovery of new potent and selective 5-HT(3) receptor antagonists.

Orvinols are potent analgesics that target opioid receptors. However, their analgesic mechanism remains unclear and no significant preference for subtype opioid receptor has been achieved. In order to find new orvinols that target the kappa-receptor, comparative 3D-QSAR studies were performed on 26 orvinol analogs using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The best predictions for the kappa-receptor were obtained with the CoMFA standard model (q2 = 0.686, r2 = 0.947) and CoMSIA model combined steric, electrostatic, hydrophobic, and hydrogen bond donor/acceptor fields (q2 = 0.678, r2 = 0.914). The models built were further validated by a test set made up of seven compounds, leading to predictive r2 values of 0.672 for CoMFA and 0.593 for CoMSIA. The study could be helpful for designing and prepare new category kappa-agonists from orvinols.

Molecular docking has been performed to investigate the binding mode of (-)-meptazinol (MEP) with acetylcholinesterase (AChE) and to screen bis-meptazinol (bis-MEP) derivatives for preferable synthetic candidates virtually. A reliable and practical docking method for investigation of AChE ligands was established by the comparison of two widely used docking programs, FlexX and GOLD. In our hands, we had more luck using GOLD than FlexX in reproducing the experimental poses of known ligands (RMSD<1.5 A). GOLD fitness values of known ligands were also in good agreement with their activities. In the present GOLD docking protocol, (-)-MEP seemed to bind with the enzyme catalytic site in an open-gate conformation through strong hydrophobic interactions and a hydrogen bond. Virtual screening of a potential candidate compound library suggested that the most promising 15 bis-MEP derivatives on the list were mainly derived from (-)-MEP with conformations of (S,S) and (SR,RS) and with a 2- to 7-carbon linkage. Although there are still no biological results to confirm the predictive power of this method, the current study could provide an alternate tool for structural optimization of (-)-MEP as new AChE inhibitors. [Figure: see text].