Browsing by Author "Sayiner, Hakan Sezgin"

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Analysis of DNA protection, interaction and antimicrobial activity of isatin derivatives.
(2019-02-01T00:00:00Z) Ganim, Mohamed Abdulhamid; Baloglu, Mehmet Cengiz; Aygun, Aysenur; Altunoglu, Yasemin Celik; Sayiner, Hakan Sezgin; Kandemirli, Fatma; Sen, Fatih
Isatin, thiosemicarbazone and their derivatives have been widely used in biological applications such as antimicrobial, antiviral and anticancer therapies. Herein, eight isatin and thiosemicarbazone derivative compounds were re-synthesized and evaluated for DNA binding analysis including DNA protection studies using plasmid DNA (pUC19) and DNA interaction experiments using calf thymus DNA (CT-DNA). All compounds were also utilized in vitro assay to assess the antimicrobial activity of compounds against different pathogenic bacterial strains. All isatin and thiosemicarbazone derivative compounds exhibited DNA protection activity which ranged from 23.5 to 59.5%. Among them, I3-(N-2-MP)-TSC had the greatest DNA protective activity. For DNA binding analysis, all compounds had the same constant concentration (40 μM), which interacts with CT-DNA. It was also observed that DNA interactions gave a high intrinsic binding constant (Kb = 1.72 × 10 M-9.73 × 10 M). Besides, several derivatives of isatin thiosemicarbazone exhibited significant and selective antibacterial activity with low concentration. These compounds primarily affected Gram-positive bacteria, but were not effective against P. vulgaris and E. coli. The Gram-positive methicillin-resistant S. aureus ATCC 43300 (MRSA) was the most influenced strain by these compounds. It was found that methyphenyl group at isatin was essential for its antibacterial activity for MRSA.
Electronic-topological and neural network approaches to the structure- antimycobacterial activity relationships study on hydrazones derivatives.
(2014) Kandemirli, Fatma; Vurdu, Can Dogan; Basaran, Murat Alper; Sayiner, Hakan Sezgin; Shvets, Nathaly; Dimoglo, Anatholy; Kovalish, Vasyl; Polat, Turgay
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.
(2018-04-07) Sayiner, Hakan Sezgin; Abdalrahm, Afaf A S; Basaran, Murat A; Kovalishyn, Vasyl; Kandemirli, Fatma
Acinetobacter is a Gram-negative, catalase-positive, oxidase-negative, non-motile, and no fermenting bacteria.