Researcher:
Dağlıyan, Onur

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Master Student

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Onur

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Dağlıyan

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Dağlıyan, Onur

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2009 - 200912010 - 20124

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Researcher Of Publications: search.filters.isAuthorOfPublication.4d4f478a-5d53-4e0e-b3ef-596f3c5ea5b7

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    Classification of cytochrome P450 inhibitors with respect to binding free energy and pIC50 using common molecular descriptors
    (Amer Chemical Soc, 2009) N/A; Department of Chemical and Biological Engineering; Department of Industrial Engineering; Dağlıyan, Onur; Kavaklı, İbrahim Halil; Türkay, Metin; Master Student; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; 40319; 24956
    Virtual screening of chemical libraries following experimental assays of drug candidates is a common procedure in structure based drug discovery. However, the relationship between binding free energies and biological activities (pIC(50)) of drug candidates is sfill an unsolved issue that limits the efficiency and speed of drug development processes. In this study, the relationship between them is investigated based on a common molecular descriptor set for human cytochrome P450 enzymes (CYPs). CYPs play an important role in drug-drug interactions, drug metabolism, and toxicity. Therefore, in silico prediction of CYP inhibition by drug candidates is one of the major considerations in drug discovery. The combination of partial leastsquares regression (PLSR) and a variety of classification algorithms were employed by considering this relationship as a classification problem. Our results indicate that PLSR with classification is a powerful tool to predict more than one output such as binding free energy and pIC(50) simultaneously. PLSR with mixedinteger linear programming based hyperboxes predicts the binding free energy and pIC(50) with a mean accuracy of 87.18% (min: 81.67% max: 97.05%) and 88.09% (min: 79.83% max: 92.90%), respectively, for the cytochrome p450 superfamily using the common 6 molecular descriptors with a 10-fold cross- val idati on.
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    Structure based drug design for insulin degrading enzyme (IDE)
    (AICHE, 2010) Department of Industrial Engineering; Department of Chemical and Biological Engineering; Department of Chemical and Biological Engineering; Türkay, Metin; Kızılel, Seda; Kavaklı, İbrahim Halil; Dağlıyan, Onur; Dağyıldız, Ezgi; Çakır, Bilal; Faculty Member; Faculty Member; Faculty Member; Master Student; PhD Student; PhD Student; Department of Industrial Engineering; Department of Chemical and Biological Engineering; College of Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; 24956; 28376; 40319; N/A; N/A; N/A
    Insulin-degrading enzyme (IDE) is an allosteric Zn +2 metalloprotease involved in the degradation of many peptides including amyloid beta (Aβ), and insulin that play key roles in Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM), respectively. Crystal structure of IDE revealed that N-terminal of IDE has an exosite which serves as a regulation site by orientation of the substrates of IDE to the catalytic site. It is plausible to find small molecules that bind to the exosite of IDE and enhance its proteolytic activity towards different substrates. In this study, we have taken a computer-aided structure based drug design methods combined with experimental methods, one novel molecule that enhances the activity of human IDE was discovered. The novel compound, designated as D10 enhanced both IDE mediated proteolysis of substrate V and insulin degradation. This study describes the first examples of a computer-aided discovery of IDE regulators, showing that in vitro activation of this important enzyme with drug-like small molecules is attainable.
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    Structure based discovery of small molecules to regulate the activity of insulin degrading enzyme
    (Current Biology Ltd, 2011) Department of Industrial Engineering; N/A; N/A; Department of Chemical and Biological Engineering; Department of Chemical and Biological Engineering; N/A; Türkay, Metin; Çakır, Bilal; Dağlıyan, Onur; Kavaklı, İbrahim Halil; Kızılel, Seda; Dağyıldız, Ezgi; Faculty Member; PhD Student; Master Student; Faculty Member; Faculty Member; PhD Student; Department of Industrial Engineering; Department of Chemical and Biological Engineering; College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; Graduate School of Sciences and Engineering; 24956; N/A; N/A; 40319; 28376; N/A
    Insulin-degrading enzyme (IDE) is an allosteric Zn +2 metalloprotease involved in the degradation of many peptides including amyloid beta (Aβ), and insulin that play key roles in Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM), respectively. Crystal structure of IDE revealed that N-terminal of IDE has an exosite which is ∼30 Å away from the catalytic region and serves as a regulation site by orientation of the substrates of IDE to the catalytic site. In this study, we applied structure based drug design methodology to discover novel small molecule organic compounds that enhance the activity of human IDE. The activity of novel compounds were tested using in vitro essays by enhanced IDE mediated proteolysis of substrate V, insulin and FAβB degradation, respectively. These compounds demonstrated submicromolar activation. In addition, amino acid mutations at the exosite of IDE verifies that the designed molecules bind to the targeted area. This study describes the first examples of a computer-aided discovery of IDE regulators, showing that in vitro activation of this important enzyme with small molecules is possible.
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    PublicationOpen Access
    Optimization based tumor classification from microarray gene expression data
    (Public Library of Science, 2011) Üney-Yüksektepe, Fadime; Department of Chemical and Biological Engineering; Department of Industrial Engineering; Dağlıyan, Onur; Kavaklı, İbrahim Halil; Türkay, Metin; Master Student; Faculty Member; Department of Chemical and Biological Engineering; Department of Industrial Engineering; College of Engineering; N/A; 40319; 24956
    Background: An important use of data obtained from microarray measurements is the classification of tumor types with respect to genes that are either up or down regulated in specific cancer types. A number of algorithms have been proposed to obtain such classifications. These algorithms usually require parameter optimization to obtain accurate results depending on the type of data. Additionally, it is highly critical to find an optimal set of markers among those up or down regulated genes that can be clinically utilized to build assays for the diagnosis or to follow progression of specific cancer types. In this paper, we employ a mixed integer programming based classification algorithm named hyper-box enclosure method (HBE) for the classification of some cancer types with a minimal set of predictor genes. This optimization based method which is a user friendly and efficient classifier may allow the clinicians to diagnose and follow progression of certain cancer types. Methodology/Principal Findings: We apply HBE algorithm to some well known data sets such as leukemia, prostate cancer, diffuse large B-cell lymphoma (DLBCL), small round blue cell tumors (SRBCT) to find some predictor genes that can be utilized for diagnosis and prognosis in a robust manner with a high accuracy. Our approach does not require any modification or parameter optimization for each data set. Additionally, information gain attribute evaluator, relief attribute evaluator and correlation-based feature selection methods are employed for the gene selection. The results are compared with those from other studies and biological roles of selected genes in corresponding cancer type are described. Conclusions/Significance: The performance of our algorithm overall was better than the other algorithms reported in the literature and classifiers found in WEKA data-mining package. Since it does not require a parameter optimization and it performs consistently very high prediction rate on different type of data sets, HBE method is an effective and consistent tool for cancer type prediction with a small number of gene markers.
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    PublicationOpen Access
    Structure based discovery of small molecules to regulate the activity of human insulin degrading enzyme
    (Public Library of Science, 2012) Department of Chemical and Biological Engineering; Department of Industrial Engineering; Çakır, Bilal; Dağlıyan, Onur; Dağyıldız, Ezgi; Barış, İbrahim; Kavaklı, İbrahim Halil; Kızılel, Seda; Türkay, Metin; PhD Student; Master Student; PhD Student; Teaching Faculty; Faculty Member; Faculty Member; Department of Chemical and Biological Engineering; Department of Industrial Engineering; College of Engineering; N/A; N/A; N/A; 111629; 40319; 28376; 24956
    Background: Insulin-degrading enzyme (IDE) is an allosteric Zn+2 metalloprotease involved in the degradation of many peptides including amyloid-beta, and insulin that play key roles in Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM), respectively. Therefore, the use of therapeutic agents that regulate the activity of IDE would be a viable approach towards generating pharmaceutical treatments for these diseases. Crystal structure of IDE revealed that N-terminal has an exosite which is similar to 30 angstrom away from the catalytic region and serves as a regulation site by orientation of the substrates of IDE to the catalytic site. It is possible to find small molecules that bind to the exosite of IDE and enhance its proteolytic activity towards different substrates.Methodology/Principal Findings: In this study, we applied structure based drug design method combined with experimental methods to discover four novel molecules that enhance the activity of human IDE. The novel compounds, designated as D3, D4, D6, and D10 enhanced IDE mediated proteolysis of substrate V, insulin and amyloid-b, while enhanced degradation profiles were obtained towards substrate V and insulin in the presence of D10 only. Conclusion/Significance: This paper describes the first examples of a computer-aided discovery of IDE regulators, showing that in vitro and in vivo activation of this important enzyme with small molecules is possible.