Green synthesis approach for new Schiff's-base complexes; theoretical and spectral based characterization with in-vitro and in-silico screening.

• Synthesized Schiff base complexes were studied by available tools. • A conductometry study was carried out in order to extract important parameters. • In vitro tests were performed on bacteria, fungus, free radicals, and cancer cell lines. • To strengthen the study, extensive theoretical implementations were carried out. Ball milling was used to obtain new Schiff-base complexes from Co(II), Fe(III), Ni(II), and Zn(II) ions in their solid form, which is considered a green method of preparation. Several spectroscopic (IR, UV–Vis, 1H NMR, Mass, SEM, EDX, XRD) and analytical approaches were used to suggest the geometries of isolated compounds. Coats–Redfern and Horowitz–Metzger methods were used to compute the kinetic and thermodynamic parameters of Zn(II) complex (i.e.). Furthermore, conductometry was used to estimate both formation/association constants of Co(II) complex (i.e.) in solution at 290.15 K. The feature of the complex in solution may offer a good view about it in its solid state. Standard methods were applied to test the antibacterial activity of ligand and complexes to TOS aureus, E. coli and Candida albicans fungus. To assess their inhibitory effect, ABTS-antioxidant screening and cytotoxicity against liver cancer cells (HepG2) were also performed. Most complexes showed mild to considerable activity towards the selected microorganisms and liver cancer cell line, respectively. The structural forms were optimized using molecular modeling, which then confirmed the binding mechanism provided by spectral analyses. To investigate the degree of inhibition for new drugs versus three selected proteins (1dee, 5uw2 and 7jx9), two in-silico techniques were used: Pharmit link and Molecular Operating Environmental module (MOE, vs 2018). The docking patterns as well as the interaction data were acquired and analyzed. The high consistency of in-vitro and in-silico outcomes lends credence to computational treatments that must be done on developed medications before they can be used in practice. [ABSTRACT FROM AUTHOR]