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The recent research focused on the green synthesis of silicon dioxide nanoparticles, SiO2@Cellulose of Zizyphus Spina-Christi nanocomposites, and L-Arginine@SiO2@Cellulose of Zizyphus Spina-Christi nanocomposites using cellulose of Zizyphus Spina-Christi as a new green polymeric surfactant. The structures of nanoparticles and nanocomposites were characterized by different spectroscopy and microscopy techniques. Nanoparticles and nanocomposites were utilized to determine the concentration of chromium, cadmium, and lead in COVID-19 patients using double-vortex-ultrasonic assisted surfactant enhanced dispersive liquid-liquid microextraction. Mean recoveries of chromium, cadmium, and lead were obtained in the range of 86-98% with relative standard deviations below 4%. The advantages of the proposed method are green and novel polymer surfactant with low detection limit. Finally, antibacterial activities were investigated. The maximum inhibition zone of L-Arginine@SiO2@Cellulose of Zizyphus Spina-Christi nanocomposites was obtained for Staphylococcus Aureus (21.9±0.4 mm). L-Arginine@SiO2@Cellulose of Zizyphus Spina-Christi nanocomposites have low cytotoxicity against MCF-7 cancer cells. These results indicated the potential ability of LArginine@ SiO2@Cellulose of Zizyphus Spina-Christi nanocomposites in the determination of metal concentrations in biological samples along with good antibacterial properties and cytotoxic properties. [ABSTRACT FROM AUTHOR]

Carbazoles and imidazole represent two important classes of heterocycles which exhibit diverse biological activities such as antitumor properties. In this study, imidazole (C1-C3) and carbazole (C4 and C5) derivatives were evaluated for their cytotoxic activity against three human cancer cell lines namely, MCF7 (human breast cancer), HT29 (human colon cancer), and HeLa (human cervical cancer). Carbazole derivatives (C4 and C5) with IC50 < 10 µM showed greater cytotoxic effect than imidazole derivatives (C1-C3). Furthermore, all compounds exhibited better anticancer activity against MCF-7 than other two cell lines (HT-29, HeLa) and compound C4 was the most potent compound with the IC50 values of 2.5, 5.4 and 4.0 µM, against MCF-7, Hela and HT-29 cell lines, respectively. Physicochemical properties of compounds were calculated and their correlation with the IC50 values on MCF-7 cell line investigated. Surface area and polarizability of compounds showed good correlation by R2 = 0.8396 and R2 = 0.834, respectively. Docking studies of these compounds were also performed on the DNA as proposed target to comprehend their binding interactions and binding energies. The docking energy of compounds ranged from - 11.32 to -13.48 kcal/mol. Compound C3 with energy of -13.48 kcal/mol had the highest docking energy. Docking results indicated that these compounds (C1-C5) had strong affinity in binding to the DNA. [ABSTRACT FROM AUTHOR]

Dichloroacetate (DCA) is a simple and small anticancer drug that arouses the activity of the enzyme pyruvate dehydrogenase (PDH) through inhibition of the enzyme pyruvate dehydrogenase kinases (PDK1-4). DCA can selectively promote mitochondria-regulated apoptosis, depolarizing the hyperpolarized inner mitochondrial membrane potential to normal levels, inhibit tumor growth and reduce proliferation by shifting the glucose metabolism in cancer cells from anaerobic to aerobic glycolysis. In this study, a series of DCA analogues were applied to quantitative structure-activity relationship (QSAR) analysis. A collection of chemometrics methods such as multiple linear regression (MLR), factor analysis-based multiple linear regression (FA-MLR), principal component regression (PCR), and partial least squared combined with genetic algorithm for variable selection (GA-PLS) were applied to make relations between structural characteristics and cytotoxic activities of a variety of DCA analogues. The best multiple linear regression equation was obtained from genetic algorithms partial least squares, which predict 90% of variances. Based on the resulted model, an in silico-screening study was also conducted and new potent lead compounds based on new structural patterns were designed. Molecular docking as well as protein ligand interaction fingerprints (PLIF) studies of these compounds were also investigated and encouraging results were acquired. There was a good correlation between QSAR and docking results. [ABSTRACT FROM AUTHOR]

Aromatase inhibitors (AIs) as effective candidates have been used in the treatment of hormone-dependent breast cancer. In this study, we have proposed 300 structures as potential AIs and filtered them by Lipinski's rule of five using DrugLito software. Subsequently, they were subjected to docking simulation studies to select the top 20 compounds based on their Gibbs free energy changes and also to perform more studies on the protein-ligand interaction fingerprint by AuposSOM software. In this stage, anastrozole and letrozole were used as positive control to compare their interaction fingerprint patterns with our proposed structures. Finally, based on the binding energy values, one active structure (ligand 15) was selected for molecular dynamic simulation in order to get information for the binding mode of these ligands within the enzyme cavity. The triazole of ligand 15 pointed to HEM group in aromatase active site and coordinated to Fe of HEM through its N4 atom. In addition, two p-cation interactions was also observed, one interaction between triazole and porphyrin of HEM group, and the other was 4-chloro phenyl moiety of this ligand with Arg115 residue. [ABSTRACT FROM AUTHOR]

Dichloroacetate (DCA) is a simple and small anticancer drug that arouses the activity of the enzyme pyruvate dehydrogenase (PDH) through inhibition of the enzyme pyruvate dehydrogenase kinases (PDK1-4). DCA can selectively promote mitochondria-regulated apoptosis, depolarizing the hyperpolarized inner mitochondrial membrane potential to normal levels, inhibit tumor growth and reduce proliferation by shifting the glucose metabolism in cancer cells from anaerobic to aerobic glycolysis. In this study, a series of DCA analogues were applied to quantitative structure-activity relationship (QSAR) analysis. A collection of chemometrics methods such as multiple linear regression (MLR), factor analysis-based multiple linear regression (FA-MLR), principal component regression (PCR), and partial least squared combined with genetic algorithm for variable selection (GA-PLS) were applied to make relations between structural characteristics and cytotoxic activities of a variety of DCA analogues. The best multiple linear regression equation was obtained from genetic algorithms partial least squares, which predict 90% of variances. Based on the resulted model, an in silico -screening study was also conducted and new potent lead compounds based on new structural patterns were designed. Molecular docking as well as protein ligand interaction fingerprints (PLIF) studies of these compounds were also investigated and encouraging results were acquired. There was a good correlation between QSAR and docking results.