Synthesis, characterization, and antimicrobial activity of copper(II) complexes with N,N′-propanediyl-bis-benzenesulfonamide and N,N′-ethanediyl-bis-2-methylbenzenesulfonamide
摘要:
Copper(II) complexes of new aryldisulfonamides (L (1) = N,N'-bis[(2-methylphenyl)sulfonyl]ethylenediamine) and L (2) = N,N'-propanediyl-bis-benzenesulfonamide with 1,10-phenanthroline have been synthesized and characterized by using elemental analyses, FT-IR, LCMS, conductivity, and magnetic susceptibility techniques. The structures of [Cu(phen)(2)]L-1 (1) and [CuL2(phen)(2)] (2) compounds have been determined. Complex (1) has also been characterized by single crystal X-ray diffraction. The complex (1) crystallizes in the triclinic system, space group P1, with cell constants a = 12.9353(8) , b = 13.8543(9) , c = 14.4513(10) , alpha = 103.593(5)A degrees, beta A = 113.713(5)A degrees, gamma A = 106.104(5)A degrees, and Z = 1. The antibacterial activities of synthesized compounds were studied against Gram-positive bacteria: Staphylococcus aureus, Bacillus subtilis, and B. cereus and Gram-negative bacteria: Escherichia coli, Pseudomonas aeruginosa, and Yersinia enterocolitica by microdilution (as MICs in mu g/mL) and disk diffusion (as diameter zone in mm) method. The biological activity screening showed that (1) has more activity than (2) against the tested bacteria.
Quantitative structure–activity relationships studies for prediction of antimicrobial activity of synthesized disulfonamide derivatives
摘要:
A new series of disulfonamides were synthesized and assayed as antimicrobial agents against Staphylococcus aureus, Bacillus cereus, and Escherichia coli. The quantitative structure-activity relationship analysis (QSAR) was applied to find out the correlation between experimentally evaluated antimicrobial activities with various parameters of the compounds using stepwise multiple liner regression method. The QSAR analysis revealed that the third-order average connectivity index ((3)chi(A)) was found to have negative correlation. The best QSAR models were further validated by leave-one-out method of cross-validation.