Browsing by Author "Başaran M.A."

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Electronic-topological and neural network approaches to the structure-antimycobacterial activity relationships study on hydrazones derivatives
(2015-01-01) Kandemirli F.; Vurdu C.D.; Başaran M.A.; Sayiner H.S.; Shvets N.; Dimoglo A.; Kovalish V.; Polat T.
That the implementation of Electronic-Topological Method and a variant of Feed Forward Neural Network (FFNN) called as the Associative Neural Network are applied to the compounds of Hydrazones derivatives have been employed in order to construct model which can be used in the prediction of antituberculosis activity. The supervised learning has been performed using (ASNN) and categorized correctly 84.4% of them, namely, 38 out of 45. Ph1 pharmacophore and Ph2 pharmacophore consisting of 6 and 7 atoms, respectively were found. Anti-pharmacophore features socalled "break of activity" have also been revealed, which means that APh1 is found in 22 inactive molecules. Statistical analyses have been carried out by using the descriptors, such as EHOMO, ELUMO, ΔE, hardness, softness, chemical potential, electrophilicity index, exact polarizibility, total of electronic and zero point energies, dipole moment as independent variables in order to account for the dependent variable called inhibition efficiency. Observing several complexities, namely, linearity, nonlinearity and multi-co linearity at the same time leads data to be modeled using two different techniques called multiple regression and Artificial Neural Networks (ANNs) after computing correlations among descriptors in order to compute QSAR. Computations resulting in determining some compounds with relatively high values of inhibition are presented.
The quantum chemical and QSAR studies on Acinetobacter baumannii oxphos inhibitors
(2018-05-01) Sayiner H.S.; Abdalrahm A.A.S.; Başaran M.A.; Kovalishyn V.; Kandemirli F.
Background: Acinetobacter is a Gram-negative, catalase-positive, oxidase-negative, non-motile, and no fermenting bacteria. Objective: In this study, some of the electronic and molecular properties, such as the highest occupied molecular orbital energy (EHOMO), lowest unoccupied molecular orbital energy (ELUMO), the energy gap between EHOMO and ELUMO, Mulliken atomic charges, bond lengths, of molecules having impact on antibacterial activity against A. baumannii were studied. In addition, calculations of some QSAR descriptors such as global hardness, softness, electronegativity, chemical potential, global electrophilicity, nucleofugality, electrofugality were performed. Method: The descriptors having impact on antibacterial activity against A. baumannii have been investigated based on the usage of 29 compounds employing two statistical methods called Linear Regression and Artificial Neural Networks. Results: Artificial Neural Networks obtained accuracies in the range of 83-100% (for active/inactive classifications) and q2=0.63 for regression. Conclusion: Three ANN models were built using various types of descriptors with publicly available structurally diverse data set. QSAR methodologies used Artificial Neural Networks. The predictive ability of the models was tested with cross-validation procedure, giving a q2=0.62 for regression model and overall accuracy 70-95 % for classification models.
Theoretical studies on mild steel corrosion inhibition by 5-substituted 1H-tetrazoles in acidic media
(2019-01-01) Elusta M.I.; Başaran M.A.; Kandemirli F.
In this theoretical study, calculations for the three types of the tetrazole which are 2-(1H-Tetrazole-5-yl)-3-phenylacrylonitrile, 2-(1H-Tetrazole-5-yl)-3-(4-nitrophenylacrylonitrile), and 2-(1H-Tetrazole-5-yl)-3-(4- hydroxyphenyl acrylonitrile) showing the corrosion inhibition efficiency on mild steel in 1M HCl were carried out with the Density Functional Theory (DFT) at the B3LYP functionals with the use of 6-311g (d, p) basis set. Calculated parameters such as EHOMO, ELUMO, energy gap, electronegativity (x), chemical potential (μ), hardness (η), softness (S),electrophilicity, electrofugality, nucleofugality, Proton affinity, polarizability and hyperpolarizability. The correlation and regression analysis have been conducted to determine which descriptors have effect on inhibition efficiency. Both the theoretical results and experimental data are in accordance based on the inhibition efficiency.