Synthesis, structural elucidation, and density functional theory investigation of new mononuclear Fe(III), Ni(II), and Cu(II) mixed-ligand complexes: Biological and catalase mimicking activity exploration

The present paper deals with synthesis new mononuclear 1:1:1 metal:ligand:co-ligand complexes, FeLG, NiLG, and CuLG, where L = 1-{(E)-[(4-methylphenyl)imino]methyl}-2-naphthol and G = Glycine. The synthesized complexes were characterized based on elemental analysis, Fourier transform infrared spectroscopy (FT-IR), ultraviolet-visible (UV-vis), mass spectra, molar conductance, magnetic susceptibility, and thermal analysis (TGA) in addition to stoichiometry determination via molar ratio method. The isolated metal complexes showed interesting geometry variation as tetrahedral for CuLG and octahedral for both FeLG and NiLG. The molecular structures of the titled compounds were optimized theoretically using density functional theory (DFT) approach, and the quantum chemical descriptors were calculated. The disk diffusion method was used to investigate the growth inhibition of the titled compounds aganist selected pathogenic bacterial and fungal strains. The metal complexes exhibited higher enhancement as antimicrobial candidates with lower minimum inhibitory concentration (MIC) than the free ligands, and in some cases, the complexes were closed to the standard species. Molecular docking investigation was carried out to ascertain the inhibitory action of the studied compounds against 1HNJ protein, the target enzyme for the antimicrobial agents. The results indicated that the FeLG has the highest binding affinity in comparison with other compounds. Thus, these molecules could be promising antimicrobial candidates. Furthermore, catalase mimicking activity of the complexes has been investigated. The data revealed that CuLG complex catalyzes the decomposition of hydrogen peroxide most effectively. Finally, the quantum chemical parameters of the titled complexes and other different compounds were correlated with their practical biological activity data in a trial to build a SAR model.