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

Ihsanul Arief (Akademi Farmasi Yarsi Pontianak)
Ria Armunanto (Austrian-Indonesian Centre (AIC) for Computational Chemistry, Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada)
Bambang Setiaji (Austrian-Indonesian Centre (AIC) for Computational Chemistry, Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada)
Muhammad Fachrie (Informatics Engineering Major, Faculty of Business and Information Technology, Universitas Teknologi Yogyakarta)

Molekul: Jurnal Ilmiah Kimia
Vol 11, No 2 (2016)

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.