Estrogen receptors (ERs) belong to the nuclear receptor superfamily, which play crucial roles in the human body. To date, two subtypes, ERα and ERβ, have been identified. The function and expression of both subtypes are various, stimulating the interest for discovering subtype selective ligands. However, ERα and ERβ are highly homologous. They share 56 % sequence identity in the ligand binding domain and only two pairs of residues differ in the ligand binding pocket. In this study, pharmacophore models were built for both subtypes based on 23 ERα and 24 ERβ selective ligands, respectively. It was found from these pharmacophore models that hydrophobic and hydrogen bonding interactions were essential for the subtype selectivity. The hydrogen bond donor feature in the phenol part was a favorable contribution to ERβ selectivity, whereas the one in the benzopyran part of the ligand was important for ERα selectivity. Furthermore, simulated virtual screening was performed with both subtype specific pharmacophore models. The results confirmed the reliability and discrimination ability of both models. These findings could not only be helpful for the understanding of a possible mechanism underlying ligand selectivity of ERs, but could also pave a new avenue for the discovery of novel selective ER ligands.

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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.

Three-dimensional pharmacophore models of human adenosine receptor A(₂A) antagonists were developed based on 23 diverse compounds selected from a large number of A(₂A) antagonists. The best pharmacophore model, Hypo1, contained five features: one hydrogen bond donor , three hydrophobic points and one ring aromatic. Its correlation coefficient, root mean square deviation, and cost difference values were 0.955, 0.921 and 84.4, respectively, suggested that the Hypo1 model was reasonable and reliable. This model was validated by three methods: a test set of 106 diverse compounds, a simulated virtual screening, and superimposition with the crystal structure of A(₂A) receptor. The results showed that Hypo1 was not only in agreement with the A(₂A) crystal structure and literature reports, but also well identified active A(₂A) antagonists from the virtual database. This methodology provides helpful information and a robust tool for the discovery of potent A(₂A) antagonists.