Yazar "Aksoydan, Busecan" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim Yok
    Öğe
    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.
  • Küçük Resim Yok
    Öğe
    Proposing novel MAO-B hit inhibitors using multidimensional molecular modeling approaches and application of binary QSAR models for prediction of their therapeutic activity, pharmacokinetic and toxicity properties
    (American Chemical Society, 2018) İş, Yusuf Serhat; Aksoydan, Busecan; Durdağı, Serdar; Yurtsever, Mine
    Monoamine oxidase (MAO) enzymes MAO-A and MAO-B play a critical role in the metabolism of monoamine neurotransmitters. Hence, MAO inhibitors are very important for the treatment of several neurodegenerative diseases such as Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS). In this study, 256 750 molecules from Otava Green Chemical Collection were virtually screened for their binding activities as MAO-B inhibitors. Two hit molecules were identified after applying different filters such as high docking scores and selectivity to MAO-B, desired pharmacokinetic profile predictions with binary quantitative structure activity relationship (QSAR) models. Therapeutic activity prediction as well as pharmacokinetic and toxicity profiles were investigated using MetaCore/MetaDrug platform which is based on a manually curated database of molecular interactions, molecular pathways, gene disease associations, chemical metabolism, and toxicity information. Particular therapeutic activity and toxic effect predictions are based on the ChemTree ability to correlate structural descriptors to that property using recursive partitioning algorithm. Molecular dynamics (MD) simulations were also performed to make more detailed assessments beyond docking studies. All these calculations were made not only to determine if studied molecules possess the potential to be a MAO-B inhibitor but also to find out whether they carry MAO-B selectivity versus MAO-A. The evaluation of docking results and pharmacokinetic profile predictions together with the MD simulations enabled us to identify one hit molecule (ligand 1, Otava ID: 3463218) which displayed higher selectivity toward MAO-B than a positive control selegiline which is a commercially used drug for PD therapeutic purposes.