Determination of Descriptors Which Influence the Toxicity of Organochlorine Compounds Using Qsar Method

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Massapihanhoro Ouattara Pierre
Bamba Kafoumba
N’guessan Nobel Kouakou
Ziao Nahossé

Abstract

Organochlorine Pesticides (OCP) are organic compounds obtained by the chlorination of various unsaturated hydrocarbons. They are very toxic and therefore belong to the family of persistent organic pollutants. If formerly these pesticides were used to fight against certain vectors of diseases and thus improve the productivity of the host, today they are considered as "enemy" of the environment. To understand the origin of the toxicity of organochlorine compounds, we used 73 molecules (test set: 50 and validation: 23) containing at least one chlorine atom and for which the toxicity (LogLC50) against Poecilia reticulata is known to establish QSAR models. Firstly, we used principal component analysis (PCA) to identify the best descriptors. Then, the different models were established using the method of multiple linear regression (MLR). Models established with quantum and physicochemical descriptors only showed satisfactory results. But the best model was determined with the combination of both quantum and physicochemical descriptors. The criteria of this model are as follows:

R2 = 0.939 ; R2ajusted = 0.932 ; Pvalue < 0.0001; α = 0.05

R2CV = 0.935 ; R2R2CV = 0.004 ; MCE = 0.073; F = 134.701

These criteria show that the toxicity of organochlorine compounds is well described by the combination of quantum and physicochemical descriptors namely lipophilia (LogP), polarizability (pol), entropy (S), zero-point energy (ZPE) and the number of chlorine atoms (NCl).

Keywords:
Organochlorine compounds, toxicity, QSAR, quantum descriptors and physicochemical descriptors

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How to Cite
Pierre, M. O., Kafoumba, B., Kouakou, N. N., & Nahossé, Z. (2019). Determination of Descriptors Which Influence the Toxicity of Organochlorine Compounds Using Qsar Method. Chemical Science International Journal, 27(1), 1-13. https://doi.org/10.9734/CSJI/2019/v27i130107
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Short Research Article