The effects of fluorine substitution on the chemical properties and inhibitory capacity of Donepezil anti-Alzheimer drug; density functional theory and molecular docking calculations.

Drug fluorination has the potential to reproduce useful drugs with decreasing the side effect of them. Identifying the effect of this improvement on the chemical properties and biological interactions of drug symbolizes a meaningful progress in drug design. Here the fluorination of Donepezil as an anti-Alzheimer drug, including 7 fluorinated derivatives of it, was investigated computationally. In the first part of our calculations, the most important chemical properties of drug that affects the drug efficiency were investigated by applying the M06/6-31g (d, p) and M062X/6-31g (d, p) levels of theories. Findings showed that the fluorine substitution changed the drug stability as altered the solubility and molecular polarity. Furthermore, the intramolecular hydrogen bonding, charge distribution and electron delocalization of the drug were affected by this replacement. In the second section, the effect of fluorination on the drug⋯enzyme interactions was evaluated by using two effective methods Based on the molecular docking and density functional theory (DFT) calculations fluorine substitution influenced the Donepezil⋯Acetylcholinesterase interactions. Calculated binding energies by two computational methods displayed that the fluorine replacement changed the binding affinity of drug. Finally, the most significant non-bonded interactions between drugs and involved residues were investigated by bond length data analysis.

Optimizing Cu(II) removal from aqueous solution by magnetic nanoparticles immobilized on activated carbon using Taguchi method.

This study synthesized magnetic nanoparticles (Fe(3)O(4)) immobilized on activated carbon (AC) and used them as an effective adsorbent for Cu(II) removal from aqueous solution. The effect of three parameters, including the concentration of Cu(II), dosage of Fe(3)O(4)/AC magnetic nanocomposite and pH on the removal of Cu(II) using Fe(3)O(4)/AC nanocomposite were studied. In order to examine and describe the optimum condition for each of the mentioned parameters, Taguchi's optimization method was used in a batch system and L9 orthogonal array was used for the experimental design. The removal percentage (R%) of Cu(II) and uptake capacity (q) were transformed into an accurate signal-to-noise ratio (S/N) for a 'larger-the-better' response. Taguchi results, which were analyzed based on choosing the best run by examining the S/N, were statistically tested using analysis of variance; the tests showed that all the parameters' main effects were significant within a 95% confidence level. The best conditions for removal of Cu(II) were determined at pH of 7, nanocomposite dosage of 0.1 gL(-1) and initial Cu(II) concentration of 20 mg L(-1) at constant temperature of 25 °C. Generally, the results showed that the simple Taguchi's method is suitable to optimize the Cu(II) removal experiments.