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    Öğe
    4D-QSAR analysis and pharmacophore modeling: Electron conformational-genetic algorithm approach for penicillins
    (Pergamon-Elsevier Science Ltd, 2011) Yanmaz, Ersin; Saripinar, Emin; Sahin, Kader; Gecen, Nazmiye; Copur, Fatih
    4D-QSAR studies were performed on a series of 87 penicillin analogues using the electron conformational-genetic algorithm (EC-GA) method. In this EC-based method, each conformation of the molecular system is described by a matrix (ECMC) with both electron structural parameters and interatomic distances as matrix elements. Multiple comparisons of these matrices within given tolerances for high active and low active penicillin compounds allow one to separate a smaller number of matrix elements (ECSA) which represent the pharmacophore groups. The effect of conformations was investigated building model 1 and 2 based on ensemble of conformers and single conformer, respectively. GA was used to select the most important descriptors and to predict the theoretical activity of the training (74 compounds) and test (13 compounds, commercial penicillins) sets. The model 1 for training and test sets obtained by optimum 12 parameters gave more satisfactory results (R-training(2) = 0.861, SEtraining = 0.044, R-test(2) = 0.892, SEtest = 0.099, q(2) = 0.702, q(ext1)(2) = 0.777 and q(ext2)(2) = 0.733) than model 2 (R-training(2) = 0.774, SEtraining = 0.056, R-test(2) = 0.840, SEtest = 0.121, q(2) = 0.514, q(ext1)(2) = 0.641 and q(ext2)(2) = 0.570). To estimate the individual influence of each of the molecular descriptors on biological activity, the E statistics technique was applied to the derived EC-GA model. (C) 2011 Elsevier Ltd. All rights reserved.
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    Öğe
    Application of electron conformational-genetic algorithm approach to 1,4-dihydropyridines as calcium channel antagonists: pharmacophore identification and bioactivity prediction
    (Springer, 2012) Gecen, Nazmiye; Saripinar, Emin; Yanmaz, Ersin; Sahin, Kader
    Two different approaches, namely the electron conformational and genetic algorithm methods (EC-GA), were combined to identify a pharmacophore group and to predict the antagonist activity of 1,4-dihydropyridines (known calcium channel antagonists) from molecular structure descriptors. To identify the pharmacophore, electron conformational matrices of congruity (ECMC)-which include atomic charges as diagonal elements and bond orders and interatomic distances as off-diagonal elements-were arranged for all compounds. The ECMC of the compound with the highest activity was chosen as a template and compared with the ECMCs of other compounds within given tolerances to reveal the electron conformational submatrix of activity (ECSA) that refers to the pharmacophore. The genetic algorithm was employed to search for the best subset of parameter combinations that contributes the most to activity. Applying the model with the optimum 10 parameters to training (50 compounds) and test (22 compounds) sets gave satisfactory results (R-training(2) = 0.848, R-test(2) = 0.904, with a cross-validated q(2) = 0.780).
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    Öğe
    Pharmacophore Modelling and 4D-QSAR Study of Ruthenium(II) Arene Complexes as Anticancer Agents (Inhibitors) by Electron Conformational-Genetic Algorithm Method
    (Bentham Science Publ Ltd, 2018) Yavuz, Sevtap Caglar; Sabanci, Nazmiye; Saripinar, Emin
    Objective: The EC-GA method was employed in this study as a 4D-QSAR method, for the identification of the pharmacophore (Pha) of ruthenium(II) arene complex derivatives and quantitative prediction of activity. Methods: The arrangement of the computed geometric and electronic parameters for atoms and bonds of each compound occurring in a matrix is known as the electron-conformational matrix of congruity (ECMC). It contains the data from HF/3-21G level calculations. Compounds were represented by a group of conformers for each compound rather than a single conformation, known as fourth dimension to generate the model. ECMCs were compared within a certain range of tolerance values by using the EMRE program and the responsible pharmacophore group for ruthenium(II) arene complex derivatives was found. For selecting the sub-parameter which had the most effect on activity in the series and the calculation of theoretical activity values, the non-linear least square method and genetic algorithm which are included in the EMRE program were used. In addition, compounds were classified as the training and test set and the accuracy of the models was tested by cross-validation statistically. Results: The model for training and test sets attained by the optimum 10 parameters gave highly satisfactory results with R-training(2) = 0.817, q(2) = 0.718 and SEtraining = 0.066, q(2) (ext1) = 0.867, q(2) (ext2) = 0.849, q(2) (ext3) = 0.895, ccc(tr) = 0.895, ccc(test) = 0.930 and cc(call) = 0.905. Conclusion: Since there is no 4D-QSAR research on metal based organic complexes in the literature, this study is original and gives a powerful tool to the design of novel and selective ruthenium(II) arene complexes.