Abstract
Pesticides are toxic chemicals aimed for the destroying pest on crops. Numerous data evidence about toxicity of pesticides on aquatic organisms. Since pesticides with similar properties tend to have similar biological activities, toxicity may be predicted from structure. Their structure feature and properties are encoded my means of molecular descriptors. Molecular descriptors can capture quite simple two-dimensional (2D) chemical structures to highly complex three-dimensional (3D) chemical structures. Quantitative structure-toxicity relationship (QSTR) method uses linear regression analyses for correlation toxicity of chemical with their structural feature using molecular descriptors. Molecular descriptors were calculated using open source software PaDEL and in-house built PyMOL plugin (PyDescriptor). PyDescriptor is a new script implemented with the commonly used visualization software PyMOL for calculation of a large and diverse set of easily interpretable molecular descriptors encoding pharmacophoric patterns and atomic fragments. PyDescriptor has several advantages like free and open source, can work on all major platforms (Windows, Linux, MacOS). QSTR method allows prediction of toxicity of pesticides without experimental assay. In the present work, QSTR analysis for toxicity of a dataset of mixtures of 5 classes of pesticides comprising has been performed.
Highlights
Pesticides are used extensively to control agricultural pest and to improve crop yields
The contamination of water by pesticides increasing around the world, so the knowledge of eco-toxicological effects for aquatic organisms for the environmental risk assessment is essential
quantitative structure-toxicity relationship (QSTR) method allows prediction of environmental toxicity derived from the molecular structure and fills an important gap in risk assessment studies (REACH) [3]
Summary
Pesticides are used extensively to control agricultural pest and to improve crop yields. The contamination of water by pesticides increasing around the world, so the knowledge of eco-toxicological effects for aquatic organisms for the environmental risk assessment is essential. Before pesticides are registered they must undergo laboratory testing on animals for short-term (acute) and long-term (chronic) health effects. Small planktonic crustaceans Daphnia, fish, and algae are the most common organisms tested for the evaluation of toxic effects of pesticides. In order to reduce expensive and time-consuming experiments and reduce animal testing quantitative structure-toxicity relationship (QSTR) method is valuable [2]. QSTR method allows prediction of environmental toxicity derived from the molecular structure and fills an important gap in risk assessment studies (REACH) [3]
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