4.7 Article

The Universal 3D QSAR Model for Dopamine D2 Receptor Antagonists

期刊

出版社

MDPI
DOI: 10.3390/ijms20184555

关键词

3D-QSAR; CoMFA model; dopamine D-2 receptor; dopamine D-2 receptor antagonists

资金

  1. OPUS grant from National Science Center (NCN, Poland) [2017/27/B/NZ7/01767]
  2. Interdisciplinary Center for Mathematical and Computational Modeling (ICM),Warsaw, Poland [G30-18]

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In order to search for novel antipsychotics acting through the D-2 receptor, it is necessary to know the structure-activity relationships for dopamine D-2 receptor antagonists. In this context, we constructed the universal three-dimensional quantitative structure-activity relationship (3D-QSAR) model for competitive dopamine D-2 receptor antagonists. We took 176 compounds from chemically different groups characterized by the half maximal inhibitory concentration (IC50) from the CHEMBL database and docked them to the X-ray structure of the human D-2 receptor in the inactive state. Selected docking poses were applied for Comparative Molecular Field Analysis (CoMFA) alignment. The obtained CoMFA model is characterized by a cross-validated coefficient Q(2) of 0.76 with an optimal component of 5, R-2 of 0.92, and an F value of 338.9. The steric and electrostatic field contributions are 67.4% and 32.6%, respectively. The statistics obtained prove that the CoMFA model is significant. Next, the IC50 of the 16 compounds from the test set was predicted with R-2 of 0.95. Finally, a progressive scrambling test was carried out for additional validation. The CoMFA fields were mapped onto the dopamine D-2 receptor binding site, which enabled a discussion of the structure-activity relationship based on ligand-receptor interactions. In particular, it was found that one of the desired steric interactions covers the area of a putative common allosteric pocket suggested for some other G protein-coupled receptors (GPCRs), which would suggest that some of the known dopamine receptor antagonists are bitopic in their essence. The CoMFA model can be applied to predict the potential activity of novel dopamine D-2 receptor antagonists.

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