Density Functional Theory (B3LYP/6-31G*) Study of Toxicity of Polychlorinated Dibenzofurans
International Journal of Computational and Theoretical Chemistry
Volume 5, Issue 2, March 2017, Pages: 14-24
Received: Feb. 25, 2017;
Accepted: Mar. 22, 2017;
Published: Apr. 13, 2017
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Sabitu Babatunde Olasupo, Department of Chemistry, Kano University of Science and Technology, Wudil Kano, Nigeria
Adamu Uzairu, Department of Chemistry, Ahmadu Bello University, Zaria, Nigeria
Balarabe Sarki Sagagi, Department of Chemistry, Kano University of Science and Technology, Wudil Kano, Nigeria
Quantitative Structure Toxicity Relationship (QSTR) study was applied to a dataset of 35 polychlorinated dibenzofurans (PCDFs) to investigate the relationship between toxicities of the compounds and their structures by employing Density Functional Theory (DFT) (B3LYP/6-31G*) method to compute their quantum molecular descriptors. The model was built using Genetic Function Algorithm (GFA) approach. The model (N= 24, Friedman LOF = 0.361, squared correlation coefficient (R2) = 0.963, R2adj = 0.955, cross-validation correlation coefficient (Q2) = 0.889, external prediction ability (R2pred) = 0.8286, P-value of optimization at P95% < 0.05) of the best statistical significance was selected. The accuracy of the model was evaluated through Leave one out (LOOV) cross-validation, external validation using test set molecules, Y-randomization and applicability domain techniques. The results of the present study are expected to be useful to the environmental regulatory agencies locally and internationally in the area of environmental risk assessment of toxicity of Polychlorinated dibenzofurans (PCDFs) and other related Polychlorinated aromatic compounds/ pollutants that fall within the model’s applicability domain.
Sabitu Babatunde Olasupo,
Balarabe Sarki Sagagi,
Density Functional Theory (B3LYP/6-31G*) Study of Toxicity of Polychlorinated Dibenzofurans, International Journal of Computational and Theoretical Chemistry.
Vol. 5, No. 2,
2017, pp. 14-24.
S. C. Basak, G. D. Grunwald, B. D. Gute, K. Balasubramanian, D. Opitz, J. Chem. Inf. Comput sci. 2013, 40, 885.
M. Tysklind, K. Lundgreen, C. Rappe, L. Eriksson, M. Jonsson, Environ toxicol chem. 2013, 12, 659.
S. Safe, L. Safe, M. Mullin, Polychlorinated Biphenyls (PCBs): Springer-Verlag: Berlin. 2015.
T. Ohura, M. Morita, R. Kuruto-Niwa, T. Amagai, H. Sakakibara, K. Shimo, Environ. Toxicol. 2010, 25,180.
S. Chu, M. Zheng, X. Xu: Characterization of the combustion products of polyethylene, Chemosphere. 2015, 39, 1497-1512.
S. M. Hay, L. L. Aylward: Dioxin risks in perspective: post, present and future, Regul. Toxico Pharmcol. 2015, 37, 202-217.
F. X. Li, C. Liu, L. Zhang, Y. Liping, J. Zhao, H. Wu; Environmental toxicology and pharmacology. 2016, 32, 278-485.
Netzeva TI, Worth AP, Aldenberg T, Benigni R, Cronin MTD, Gramatica P, Jaworska JS, Kahn S, Klopman G, Marchant CA, Myatt G, Nikolova-Jeliazkova N, Patlewicz GY, Perkins R, Roberts DW, Schultz TW, Stanton DT, van de Sandt JJM, Tong WD, Veith G, Yang CH, Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships-The report and recommendations of ECVAM Workshop 52. Atla-Alternatives to Laboratory Animals. 2015, 33:155-173.
A. Ashek, C. Lee, H. Park, S. J. Cho, 3D QSAR studies of dioxins and dioxin-like compounds using CoMFA and CoMSIA Chemosphere. 2013, 65,521-529.
O. G. Mekenyan, D. J. Veith, G. T. A Ankley, QSAR evaluation of Ah receptor bonding of halogenated aromatic Exnobiotics. Environ Health Perpect. 2013, 104, 1302-1310.
CS Chem3D Ultra Cambridge soft corporation, Cambridge USA, 2014.
WAREFUNCTION, Inc. Spartai 14 version 1.1.2, Irvine, California, USA. 2013.
J. P. Ameji, A. Uzairu, S. O. Idris. J. Comput. Methods Mol. Des. 2015, 5, 120.
J. Holland, University of Michigan Press, Adaptation in Natural and Artificial systems, 1975/1992.
W Wu, C. Zhang, W. ling, Q. chen, X. Guo, Y. Qian, PLOS ONE, 2015, 10, 3.
R Kunal; P P Roy; S Paul; I Mitra, Molecules. 2009, 14, 1660-1701.
Ravinchandran, V.; Rajak, H.; Jain, A.; Sivadasan, S.; Varghese, C. P.; Kishore-Agrawal, P. Int J. of Design and Discovery. 2011, 2, 511-519.
P. Ambure, R. B. Aher, A. Gajewicz, T. Puzyn, K. Roy, Chemometrics and Intelligent Laboratory Systems. 2015, 147, 1-13.
Emilia Amzoiu, Paul Gabriel Anoaica, Costinel I. Lepădatu. QSAR Study of Toxicity of Aromatic nitro derivatives using the electronegativity of Omo/Umo States as Fingerprint Descriptors. Revue Roumaine De Chimie. 2011, 56(7), 711-716.
Falandysz J., T. Puzyn1, B. Szymanowska1, M. Kawano, M. Markuszewski, R. Kaliszan, P. Skurski, J. Błażejowski4, T. Wakimoto, Thermodynamic and Physico-Chemical Descriptors of Chloronaphthalenes: An Attempt to Select Features Explaining Environmental Behaviour and Specific Toxic Effects of These Compounds. Polish Journal of Environmental Studies.2001, 10 (4); 217-235.
Hassan Samuel; Adamu Uzairu; Paul Andrew Mamza; Okunola Oluwale Joshua. Genetic Functional Algorithm Prediction of Toxicity of some Polychlorinated Dioxins using DFT and Semi-empirical Calculated Molecular Descriptors. International Journal of Pharma Sciences and Research, 2016, 7(3); 114-125.
Lipinski, C. A., Lombardo, F., Dominy, B. W. and Feeney, P. J., Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings, Adv DrugDeliv Rev. 2001, 46, 3-26.
Van de Waterbeemd, H. and Gifford, E., ADMET in silico modelling: towards prediction paradise? Nat Rev Drug Discov. 2003, 2, 192-204.