DESIGN OF LOW CYTOTOXICITY DIARYLANILINE DERIVATIVES BASED ON QSAR RESULTS: AN APPLICATION OF ARTIFICIAL NEURAL NETWORK MODELLING

Abstract

Study on cytotoxicity of diarylaniline derivatives by using quantitative structure-activity relationship (QSAR) has been done. The structures and cytotoxicities of diarylaniline derivatives were obtained from the literature. Calculation of molecular and electronic parameters was conducted using Austin Model 1 (AM1), Parameterized Model 3 (PM3), Hartree-Fock (HF), and density functional theory (DFT) methods. Artificial neural networks (ANN) analysis used to produce the best equation with configuration of input data-hidden node-output data = 5-8-1, value of r2 = 0.913; PRESS = 0.069. The best equation used to design and predict new diarylaniline derivatives. The result shows that compound N1-(4′-Cyanophenyl)-5-(4″-cyanovinyl-2″,6″-dimethyl-phenoxy)-4-dimethylether benzene-1,2-diamine) is the best-proposed compound with cytotoxicity value (CC50) of 93.037 μM.