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All Journal Molekul: Jurnal Ilmiah Kimia
Bambang Setiaji
Austrian-Indonesian Centre (AIC) for Computational Chemistry, Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada
Chemical Engineering, Chemistry & Bioengineering Chemistry

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DESIGN OF LOW CYTOTOXICITY DIARYLANILINE DERIVATIVES BASED ON QSAR RESULTS: AN APPLICATION OF ARTIFICIAL NEURAL NETWORK MODELLING Ihsanul Arief; Ria Armunanto; Bambang Setiaji; Muhammad Fachrie
Molekul Vol 11, No 2 (2016)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (587.967 KB) | DOI: 10.20884/1.jm.2016.11.2.242

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.
Co-Authors Ihsanul Arief Muhammad Fachrie Ria Armunanto