Quantitative conformationally sampled pharmacophore for delta opioid ligands: reevaluation of hydrophobic moieties essential for biological activity

Abstract

Recent studies have indicated several therapeutic applications for delta opioid agonists and antagonists. To exploit the therapeutic potential of delta opioids developing a structural basis for the activity of ligands at the delta opioid receptor is essential. The conformationally sampled pharmacophore (CSP) method (Bernard et al. J. Am. Chem. Soc. 2003, 125, 3103-3107) is extended here to obtain quantitative models of delta opioid ligand efficacy and affinity. Quantification is performed via overlap integrals of the conformational space sampled by ligands with respect to a reference compound. Iterative refinement of the CSP model identified hydrophobic groups other than the traditional phenylalanine residues as important for efficacy and affinity in DSLET and ICI 174 864. The obtained models for a structurally diverse set of peptidic and nonpeptidic delta opioid ligands offer good predictions with R2 values>0.9, and the predicted efficacy for a set of test compounds was consistent with the experimental values.

Figure 1

Non-peptidic δ opioid ligands used in the development of the quantitative efficacy and affinity models. The pharmacophore groups A in green, B in red and N in blue. Compounds 8 and 9 were included only for affinity modeling and compounds 10 - 13 were used as external tests for efficacy prediction.

Figure 2

2D probability distributions and calculated OC for, A) 1 (red) and 7 (green), and B) 1(red) and 4 (blue).

Figure 3

Examples of centroid and maximum distance based calculations of pharmacophoric parameters shown for 4. The pharmacophore groups A in green, B in red and N in blue. The lines in magenta indicate the type of measurement A) Centroid B) Maximum A-B distance (MaxD).

Figure 4

Quantitative conformationally sampled δ opioid pharmacophore (CSP) models. A) Efficacy model based on the MaxD parameter with the Leu⁵ residue in 17 and the allylic amino substituent in 18 as the pharmacophoric B group (see Table 4 for original data). B) Efficacy model based on the MaxD parameter with the Leu⁵ residue in 17 and the Leu⁵ residue in 18 as the pharmacophoric B group (see Table 5 for original data). C) Affinity model for high efficacy δ opioid ligands with the Leu⁵ residue in 17 as the pharmacophoric B group (see Table 6 for original data). D) Affinity model for low efficacy δ opioid ligands with the allylic amino substituent in 18 as the pharmacophoric B group (see Table 7 for original data). Affinity models developed using the natural logarithms of experimental values.

Figure 5

Superimposition of conformations for A) non-peptidic ligands and B) peptidic ligands identified based on the δ opioid efficacy model. The reference compound 1 is colored based on atom type in bond format. The three atoms defining the pharmacophore points (A, B & N using MaxD criterion) are shown as spheres. Remaining structures as wireframe in the following colors: A) 6 in red and 7 in purple. B) 14 in yellow, 15 in brown, 16 in purple and 17 in orange.