International Journal of Bioorganic Chemistry 2017; 2(3): 107-117 http://www.sciencepublishinggroup.com/j/ijbc doi: 10.11648/j.ijbc.20170203.15 Quantitative Structure Toxicity Relationship (QSTR) Models for Predicting Toxicity of Polychlorinated Biphenyls (PCBs) Using Quantum Chemical Descriptors Sabitu Babatunde Olasupo 1, * , Adamu Uzairu 2 , Balarabe Sarki Sagagi 1 1 Department of Chemistry, Kano University of Science and Technology, Wudil, Nigeria 2 Department of Chemistry, Ahmadu Bello University, Zaria, Nigeria Email address: olasabit@yahoo.com (S. B. Olasupo) * Corresponding author To cite this article: Sabitu Babatunde Olasupo, Adamu Uzairu, Balarabe Sarki Sagagi. Quantitative Structure Toxicity Relationship (QSTR) Models for Predicting Toxicity of Polychlorinated Biphenyls (PCBs) Using Quantum Chemical Descriptors. International Journal of Bioorganic Chemistry. Vol. 2, No. 3, 2017, pp. 107-117. doi: 10.11648/j.ijbc.20170203.15 Received: February 25, 2017; Accepted: March 22, 2017; Published: April 7, 2017 Abstract: The Density functional theory (DFT) at B 3 LYP of 6-31G* basis set was employed to optimize 30 polychlorinated Biphenyls (PCBs) involved in this study by using Genetic function appropriation algorithm (GFA) approach to develop regression models in order to predict the toxicity of the compounds. The optimum model which has squared correlation coefficient (R 2 ) = 0.9382, cross validated correlation coefficient (R 2 cv) = 0.9056, adjusted squared correlation coefficient (R 2 Adj ) = 0.9228 and external prediction (R 2 pred ) =0.7238 was selected. The robustness of the model was confirmed by method of Y- randomization and the accuracy of the proposed model was also illustrated by using cross-Validation, validation through an external test set and applicability domain techniques. This QSTR model proved to be a useful tool in the prediction of toxicity of the congeneric compounds and a guide in the identification of structural features that could be responsible for toxicity of other polychlorinated aromatic compounds. Keywords: QSAR, Dioxins, PCBs, QSTR, Polychlorinated Biphenyls 1. Introduction Polychlorinated biphenyls (PCBs) are among the most environmentally dangerous chemicals belonging to the class of polychlorinated aromatic compounds [1], ubiquitously present in every compartment of the environment including soils, sediments, plants, animals, and human beings [2]. These compounds are of environmental and human health concern, because of their wide range of acute and chronic health effects on humans such as cancer, endocrine disruptors, neurological damage, reproductive disorders and immune suppression [3-4]. The physico-chemical properties exhibit by these chemicals such as hydrophobicity, low water solubility and lipophilicity, make them to accumulate in soil, sediments, biota and in humans and food webs and other indirect exposure [5-6] posing significant health threats to well-being of humans and animals [6]. Polychlorinated biphenyls are dioxin-like compounds (DLCs) formed and get released to the environment as by – products of various industrial processes which includes incomplete combustion of organic matter in industrial operations, medical waste incinerators, power plants, vehicle engines, household wood fires and forest fires [7], and are commonly regarded as highly toxic chemicals that are environmental contaminants and persistent organic pollutants (POP) [8]. Therefore, investigations on toxicity of PCBs are of great importance to understand their risk to human health and to the environment at large by making use of their toxicity data of the compounds to evaluate their risk to organisms and further adopt effective measures to reduce the adverse effects of this toxic chemical or pollutant in our environment. However, because of high cost, time-consuming process, limits of detection and lack of adequate standard materials, toxicity data are rather scarce for non-genotoxic adverse effects of compounds. In order to conquer these problems and quickly estimate the environmental behaviors of