Artificial Neural Networks based validation, DFT, thermal and biological evaluation of novel 4-aminoantipyrine derived Ru(III) complexes

Abstract

Series of novel Schiff base ruthenium complexes were synthesized using 4-aminoantipyrine derivatives. Elemental analysis and molecular mass of synthesized complexes are in agreement with calculated values. Molar conductance measurement reveals electrolytic property. Infrared spectral data reveal the ligands as tetra dentate coordinated to metal ions via imine nitrogen atom. All the complexes show octahedral geometry, which was identified by electronic spectra and magnetic measurements. Cyclic voltammetry analysis is used to identify the redox behavior of the complexes. XRD study of ligand and complexes reveal nano crystalline. The chelates exhibit high photo catalytic efficiency in UV-spectra with methylene blue dye. Thermal decomposition is in accordance with suggested formulae of the chelates. DFT computations have been used to determine the optimized molecular structure and bond parameters. The molinspiration calculations are used to identify the adherence of metal complexes to Lipinski’s rule of Five. Antibacterial screening was carried out against the bacterium B. Substilis, S. Aureus, E. Coli and K. Pneumoniae and two fungal species viz A. Niger and C. Albicans. Anticancer activity shows that the Ru(III) complexes exhibit noticeable cytotoxic effect in the SK-MEL-28 cell line. Analytical characterization was validated using Artificial Neutral Networks (ANN). New method has been adopted for automation, to get more accurate results compared to the previous existing machine learning models, the proposed Artificial Neural Networks achieved good testing accuracy.