Abstract
The dopamine D2 Receptor (D2R) is a member of the G-Protein-Coupled Receptor family and plays a critical role in neurotransmission activities in the human brain. Dysfunction in dopamine receptor signaling may lead to mental health illnesses such as schizophrenia and Parkinson’s disease. D2R is the target protein of the commonly used antipsychotic drugs such as risperidone, clozapine, aripiprazole, olanzapine, ziprasidone, and quetiapine. Due to their significant side effects and non-selective profiles, the discovery of novel drugs has become a challenge for researchers working in this field. Recently, our group has focused on the interactions of these drug molecules in the active site of the D2R using different in silico approaches. We here compare the performances of different approaches in estimating the drug binding affinities using quantum chemical approaches. Conformations of drug molecules (ligands) at the binding site of the D2R taken from the preliminary docking studies and molecular dynamics simulations were used to generate protein–ligand interaction models. In a first approach, the BSSE-corrected interaction energies of the ligands with the most critical amino acid Asp114 and with the other amino acids closest to ligands in the binding cavity were calculated separately by density functional theory method in implicit water environment at the M06-2X/6-31 g(d,p) level of the theory. In a second approach, ligand binding affinities were calculated by taking into consideration not only the interaction energies but also deformation and desolvation energies of ligands with surrounding amino acid residues, in a radius of 5 Å of the protein-bound ligand. The quantum mechanically obtained results were compared with the experimentally obtained binding affinity values. We concluded that although H-bond interactions of ligands with Asp114 are the most dominant interaction in the binding site, if van der Waals and steric interactions of ligands which have cumulative effect on the ligand binding are not included in the calculations, the interaction energies are overestimated.
Original language | English |
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Pages (from-to) | 2668-2677 |
Number of pages | 10 |
Journal | Journal of Biomolecular Structure and Dynamics |
Volume | 36 |
Issue number | 10 |
DOIs | |
Publication status | Published - 27 Jul 2018 |
Bibliographical note
Publisher Copyright:© 2017, © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Funding
This work was supported by the Max Planck Society for the Advancement of Science, the ‘Center for Dynamic Systems: Systems Engineering’ (an excellence initiative by Saxony-Anhalt and ERDF) and the Research Fund of Istanbul Technical University. Computing resources are provided by the National Center for High Performance Computing of Turkey (UHEM) under the Grant Number 5004452017. This work was supported by the Max Planck Society for the Advancement of Science, the ?Center for Dynamic Systems: Systems Engineering? (an excellence initiative by Saxony-Anhalt and ERDF) and the Research Fund of Istanbul Technical University. Computing resources are provided by the National Center for High Performance Computing of Turkey (UHEM) under the Grant Number 5004452017. We thank the Max Planck Society for the Advancement of Science and the Center for Dynamic Systems: Systems Engineering (an excellence initiative by Saxony-Anhalt and ERDF) for financial support.
Funders | Funder number |
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Max Planck Society for the Advancement of Science | |
Max-Planck-Gesellschaft | |
Istanbul Teknik Üniversitesi | 5004452017 |
European Regional Development Fund |
Keywords
- computer aided drug design
- DFT
- GPCRs
- ligand binding affinities
- Protein–ligand interactions
- quantum mechanics calculations