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    A QM protein-ligand investigation of antipsychotic drugs with the dopamine D2 Receptor (D2R)
    (Taylor & Francis Inc, 2018) Salmas, Ramin Ekhteiari; Is, Yusuf Serhat; Durdagi, Serdar; Stein, Matthias; Yurtsever, Mine
    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 angstrom 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.
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    Integrated Binary QSAR-Driven Virtual Screening and In Vitro Studies for Finding Novel hMAO-B-Selective Inhibitors
    (Amer Chemical Soc, 2020) Is, Yusuf Serhat; Aksoydan, Busecan; Senturk, Murat; Yurtsever, Mine; Durdagi, Serdar
    The increased activity of monoamine oxidase (MAO) enzymes may lead to serious consequences since they reduce the level of neurotransmitters and are associated with severe neurodegenerative diseases. The inhibition of this enzyme, especially the B isoform, plays a vital role in the treatment of Parkinson's disease (PD). This study is aimed to find novel human MAO-B (hMAO-B) selective inhibitors. A total of 256.750 compounds from the Otava small molecules database were virtually screened gradually by employing several screening techniques for this purpose. Initially, a high-throughput virtual screening (HTVS) method was employed, and 10% of the molecules having high docking scores were subjected to binary QSAR models for further screening of their therapeutic activities against PD, Alzheimer's disease (AD), and depression as well as for their toxicity and pharmacokinetic properties. Then, enzyme selectivity of the ligands towards the A and B forms that passed through all the filters were studied using the induced-fit docking method and molecular dynamics simulations. At the end of this exhaustive research, we identified two hit molecules ligand3 (Otava ID: 7131545) and ligand4 (Otava ID: 7566820). Based on the in vitro results, these two compounds (ligands3 and 4) together with ligands 1 and 2 found in our previous study showed activity at the nanomolar (nM) level, and the results indicated that these four ligands inhibit hMAO-B better than the FDA-approved drug selegiline.