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Article

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

1
Gachon Institute of Pharmaceutical Science & Department of Pharmacy, College of Pharmacy, Gachon University, 191 Hambakmoeiro, Yeonsu-gu, Incheon 21936, Korea
2
CimplSoft, Thousand Oaks, CA 91320, USA
3
CimplRx, Euni-ro, Seoul 06764, Korea
*
Author to whom correspondence should be addressed.
Molecules 2018, 23(10), 2452; https://doi.org/10.3390/molecules23102452
Received: 22 July 2018 / Revised: 14 September 2018 / Accepted: 21 September 2018 / Published: 25 September 2018
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: R2training = 0.80; AHPRRR104: R2training = 0.82) and predictability (APRRR215: Q2test = 0.73, R2predictive = 0.82; AHPRRR104: Q2test = 0.86, R2predictive = 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. View Full-Text
Keywords: pharmacophore; 3D-QSAR; virtual screening; D3R selective antagonist; molecular docking; CNS-like pharmacophore; 3D-QSAR; virtual screening; D3R selective antagonist; molecular docking; CNS-like
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MDPI and ACS Style

Lee, J.H.; Cho, S.J.; Kim, M.-h. Discovery of CNS-Like D3R-Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening. Molecules 2018, 23, 2452. https://doi.org/10.3390/molecules23102452

AMA Style

Lee JH, Cho SJ, Kim M-h. Discovery of CNS-Like D3R-Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening. Molecules. 2018; 23(10):2452. https://doi.org/10.3390/molecules23102452

Chicago/Turabian Style

Lee, June Hyeong, Sung Jin Cho, and Mi-hyun Kim. 2018. "Discovery of CNS-Like D3R-Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening" Molecules 23, no. 10: 2452. https://doi.org/10.3390/molecules23102452

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