Discovery of CNS-Like D3R-Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening

Abstract

The dopamine D3 receptor is an important CNS target for the treatment of a variety of neurological diseases. Selective dopamine D3 receptor antagonists modulate the improvement of psychostimulant addiction and relapse. In this study, five and six featured pharmacophore models of D3R antagonists were generated and evaluated with the post-hoc score combining two survival scores of active and inactive. Among the Top 10 models, APRRR215 and AHPRRR104 were chosen based on the coefficient of determination (APRRR215: R²_training = 0.80; AHPRRR104: R²_training = 0.82) and predictability (APRRR215: Q²_test = 0.73, R²_predictive = 0.82; AHPRRR104: Q²_test = 0.86, R²_predictive = 0.74) of their 3D-quantitative structure⁻activity relationship models. Pharmacophore-based virtual screening of a large compound library from eMolecules (>3 million compounds) using two optimal models expedited the search process by a 100-fold speed increase compared to the docking-based screening (HTVS scoring function in Glide) and identified a series of hit compounds having promising novel scaffolds. After the screening, docking scores, as an adjuvant predictor, were added to two fitness scores (from the pharmacophore models) and predicted Ki (from PLSs of the QSAR models) to improve accuracy. Final selection of the most promising hit compounds were also evaluated for CNS-like properties as well as expected D3R antagonism.

Keywords: 3D-QSAR; CNS-like; D3R selective antagonist; molecular docking; pharmacophore; virtual screening.

Figure 1

Superimposed 3PBL protein-ligand docking of dopamine (green; endogenous D3R agonist), eticlopride (yellow; non-selective D3R antagonist) and R-22 (sky blue; selective D3R antagonist).

Figure 2

Workflows of this study.

Figure 3

Docking pose showing the interaction between R-22 and 3PBL residues. In the left-hand picture, the blue line shows Pi-Pi stacking, the purple line shows hydrogen bond interaction and the yellow-green line shows hydrophobic interaction.

Figure 4

Representative 3D-QSAR models: APRRR215 (upper) and AHPRRR104 (lower).

Figure 5

APRRR215 regression lines for the training (blue) and test (red) sets.

Figure 6

AHPRRR104 regression lines for the training (blue) and test (red) sets.

Figure 7

APRRR215 ROC curve and AUC.

Figure 8

APRRR 215 skeletal box-and-whisker plot.

Figure 9

Hit selection workflow.