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

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Ihsanul Arief, Ria Armunanto, Bambang Setiaji, Muhammad Fachrie

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.


References


Arief, I., Armunanto, R. and Setiaji, B., 2013, Study on Anti-Hiv Activity of Diarylaniline Derivatives using Quantitative Structure-Activity Relationship (QSAR), Indonesian Journal of Chemistry 13(2): 129-135.

Deeb O. and Drabh, M., 2010, Exploring QSARs of Some Analgesic Compoundsby PC-ANN, Chemical Biology and Drug Design 76: 255-262.

Deeb, O., and Jawabreh, M., 2012, Exploring QSARs for Inhibitory Activity of Cyclic Urea and Nonpeptide-Cyclic Cyanoguanidine Derivatives HIV-1 Protease Inhibitors by Artificial Neural Network, Advances in Chemical Engineering and Science 2: 82-100.

Ekins, S. and Williams, A.J., 2012, The Future of Computational Models for Predicting Human Toxicities, Altex Proceedings, 1/12, Proceedings of WC8.

Eroğlu, E., Türkmen, H., Güler, S., Palaz, S., and Oltulu, O., 2007, A DFT-Based QSARs Study of Acetazolamide/Sulfanilamide Derivatives with Carbonic Anhydrase (CA-II) Isozyme Inhibitory Activity, International Journal of Molecular Science 8: 145-155.

Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H. P.; Izmaylov, A. F.; Bloino, J.; Zheng, G.; Sonnenberg, J. L.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Montgomery, Jr., J. A.; Peralta, J. E.; Ogliaro, F.; Bearpark, M.; Heyd, J. J.; Brothers, E.; Kudin, K. N.; Staroverov, V. N.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Rega, N.; Millam, J. M.; Klene, M.; Knox, J. E.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Zakrzewski, V. G.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Dapprich, S.; Daniels, A. D.; Farkas, Ö.; Foresman, J. B.; Ortiz, J. V.; Cioslowski, J.; Fox, D. J., 2009, Gaussian 09, Revision A.02, Gaussian, Inc., Wallingford CT.

Gacche, R.N. and Jadhav, S.G., 2012, Antioxidant Activities and Cytotoxicity of Selected Coumarin Derivatives: Preliminary Results of a StructureeActivity Relationship Study Using Computational Tools, Journal of Experimental and Clinical Medicine 4(3): 165-169.

Hemmateenejad, B., Javidnia, K., Nematollahi, M., and Elyasi, M., 2009, QSAR Studies on the Antiviral Compounds of Natural Origin, Journal of Iranian Chemical Society 6(2): 420-435.

Hosseini, S., Monajjemi, M., Rajaeian, E., Haghgu, M., Salari, A. and Gholami, M.R., 2013, A Computational Study of Cytotoxicity of Substituted Amides of Pyrazine2-carboxylic acids Using QSAR and DFT Based Molecular Surface Electrostatic Potential, Iranian Journal of Pharmaceutical Research 12(4): 745-750.

Hu, R., Doucet, J., Delamar, M., and Zhang, R., 2009, QSAR Models for 2-Amino-6-Arylsulfonylbenzonitriles and Congeners HIV-1 Reverse Transcriptase Inhibitors Based on Linear and Nonlinear Regression Methods, European Journal of Medicinal Chemistry 44: 2158–2171.

HyperCube, Inc, 2011, HyperChemTM 8.0.10 for Windows, http://www.hyper.com.

IBM Corp. Released 2010. IBM SPSS Statistics for Windows, Version 19.0. Armonk, NY: IBM Corp.

Jain, S.V., Ghate, M., Bhadoriya, K.S., Bar, S.B., Chaudhari, A., and Borse, J.S., 2012, 2D, 3D-QSAR and Docking Studies of 1,2,3-Thiadiazole Thioacetanilides Analogues as Potent HIV-1 Non-Nucleoside Reverse Transcriptase Inhibitors, Organic Medicinal Chemistry Letter 2: 22-34.

Low, Y., Uehara, T., Minowa, Y., Yamada, H., Ohno, Y., Urushidani, T., Sedykh, A., Muratov, E., Kuz’min, V., Fourches, D., Zhu, H., Rusyn, I. and Tropsha, A., 2011, Predicting Drug-Induced Hepatotoxicity Using QSAR and Toaxicogenomics Approaches, Chemical Research in Toxicology 24: 1251-1262.

MATLAB (Version 7.8.0.347 (R2009a), http://www.mathworks.com.

Podunavac-Kuzmanović, S.O., Cvetković, D.D., and Barna, D.J., 2009, QSAR Analysis of 2-Amino or 2-Methyl-1-Substituted Benzimidazoles Against Pseudomonas aeruginosa, International Journal of Molecular Sciences 10 : 1670-1682.

Ruiz, P., Begluitti, G., Tincher, T., Wheeler, J. and Mumtaz, M., 2012, Prediction of Acute Mammalian Toxicity Using QSAR Methods: A Case Study of Sulfur Mustard and Its Breakdown Products, Molecules 17: 8982-9001.

Sun, H. and Scott, D.O., 2010, Structure-based Drug Metabolism Predictions for Drug Design, Chemical Biology and Drug Design 75: 3-17.

Sun, L., Zhu, L., Qian, K., Qin, B., Huang, L., Chen, C.H., Lee, K., and Xie, L., 2012, Design, Synthesis, and Preclinical Evaluations of Novel 4‑Substituted 1,5-Diarylanilines as Potent HIV‑1 Non-Nucleoside Reverse Transcriptase Inhibitor (NNRTI) Drug Candidates, Journal of Medicinal Chemistry 55: 7219-7229.

Wang, Z., Kai, Z., Beier, R.C., Shen, J. and Yang, X., 2012, Investigation of Antigen-Antibody Interactions of Sulfonamides with a Monoclonal Antibody in a Fluorescence Polarization Immunoassay Using 3D-QSAR Models, International Journal of Molecular Sciences 13: 6334-6351.




DOI: http://dx.doi.org/10.20884/1.jm.2016.11.2.242

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Molekul

Jurnal Ilmiah Kimia
Department of Chemistry, Faculty of Mathematics and Natural Sciences,
Universitas Jenderal Soedirman, Purwokerto, Indonesia

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