Computational Tools and Techniques to Predict Aquatic Toxicity of Some Halogenated Pollutants

Computational Tools and Techniques to Predict Aquatic Toxicity of Some Halogenated Pollutants

Raghunath Satpathy (Majhighariani Institute of Technology and Science, India)
DOI: 10.4018/978-1-5225-6111-8.ch018

Abstract

Halogenated organic compounds are usually xenobiotic in nature and used as ingredients for the synthesis of pesticides, solvents, surfactants, and plastics. However, their introduction to the aquatic ecosystems resulted in ecological danger due to their toxic effects. The usual method of toxicity assessment is by performing the experimental approach by considering some model organism. In this aspect the computational techniques such as QSAR (quantitative structure activity relationship) is considered an effective method. By computing several molecular features and the experimental activity, the toxic effect of a compound can be correlated. This chapter describes the aquatic toxicity of the compounds. The information about different computational resources (databases, tools, and modeling tools) have been given. Also, the application of QSAR to predict aquatic toxicity of different halogenated compounds available in the literature has been reviewed.
Chapter Preview
Top

Introduction

From the industry and agriculture sector, huge amount of halogenated organic compounds are produced (Gribble, 1994; Song et al., 2000). Due to their continuous entry into the environment, the propensity for the accumulation of these compounds in the habitats represents a global threatening (Perocco et al., 1983; Damstra, 2002; Dewan et al., 2013). Due to their persistency, many of these compounds are banned. However due to their versatility, long history of formulation and use as major industrial chemicals; these have been detected in soil, sediments as well as in water ecosystems (Persistent, 2000). Another feature in case of the halogenated pollutants is their toxicity increases with an increasing number of halogen atoms and number of aromatic rings present in the molecule (Nikinmaa, 2014). Aquatic organisms are frequently faced with periods of exposure to various environmental pollutants, often as the result of the release of chemicals from agricultural and/or industrial activities. Among them, paper and pulp mills were the major sources of halogenated compounds, especially chlorinated compounds because of chlorine bleaching (Walker & Peterson, 1994; Ali & Sreekrishnan, 2001).Different categories of halogenated compounds that are persistent and having ecotoxicological effects are polychlorinated biphenyls (PCBs), dioxins and many organochlorine insecticides (Table 1).

Table 1.
Showing the example of halogenated substances causes aquatic toxicity
S. No.Common Sources of Halogenated CompoundsRemark
1Persistent Halogenated compoundsPersistent organic pollutants (POPs) include halogenated compounds as a major component. Important examples are polychlorinated biphenyls (PCBs), dioxins (e.g. TCDD), furans, and organochlorine insecticides.
2Paper- and pulp-mill effluentsSince chlorinated compounds have disappeared from effluents, the major toxic compounds are natural compounds of trees, such as resin acids from coniferous trees and phenolics from deciduous trees
3Endocrine-disrupting compoundsThese include several types of compounds with various modes of action. Although several different types of hormonal pathways could be targeted, the term is most commonly used for compounds that disturb reproductive hormone cycles
4PesticidesPesticides contain several different types of compounds, including herbicides, insecticides, and fungicides

Key Terms in this Chapter

Statistical Modeling: A statistical model is a class of mathematical model that provides a set of assumptions concerning the generation of some sample data.

Aquatic Toxicity: Refers to the effects of a compound to organisms living in the water and is usually determined on organisms representing, usually considering in the three trophic levels, such as vertebrates (fish), invertebrates (crustaceans as Daphnia spp.), and algae.

LC 50 (Lethal Concentration 50): LC50 value is the concentration of a material in air that will kill 50% of the test subjects (animals, typically mice or rats) when administered as a single exposure (typically 1 or 4 hours).

Halogenated Compounds: Halogenated compounds are normally man-made (xenobiotic).Their toxicity increases with an increasing number of halogen moieties as well as the increasing in number of aromatic rings in the molecule.

EC50: ( Effective Concentration 50): This refers to the concentration of a toxic substances that indices 50% of mortality in cells after a specified exposure time.

Model Validation: Model validation is verification of the generated model under a guided frame work to access the performance to a desired level.

IGC50 (50% Inhibition Growth Concentration): IGC 50 inhibits the growth of cells by 50%.

Computational Techniques: Computational tools are the implemented techniques in computers to solve problems by either step-wise, repeated, and iterative solution methods; also known as in-silico methods.

Kow and Pow (N-Octanol-Water Partition Coefficients): This is widely used property for assessing the partitioning behavior of chemicals in the environment to estimate the fate, behavior, and effects of toxic chemicals in the environment.

QSAR Models: Quantitative structure-activity relationship models are regression or classification models used in the chemical and biological sciences and engineering to predict the effect by considering suitable dependent and independent variable.

Toxic Substances: A substance that can be lethal or cause health hazards when uptake by the cell or body.

Machine Learning Methods: Obtained from the study of pattern recognition and computational learning theory in artificial intelligence.

Molecular Descriptor: The molecular descriptor is quantitative chemical information encoded within a symbolic representation which is the result of some standardized experiment.

Complete Chapter List

Search this Book:
Reset