Potential Health Risks of Chloroacetanilide Herbicides: An In Silico Analysis

Abstract

The extensive use of herbicidal products in agriculture and forestry has raised concerns over potential adverse effects on human health and the environment. Chloroacetanilide herbicides are a group of synthetic chemicals used to control weeds in agriculture and forestry. However, so[me of their members have been characterized as possible carcinogens. The genotoxicity and carcinogenicity of two chloroacetanilide herbicides, delachlor and xylachlor, are discussed. This article proposes to use tools to predict their potential toxicities based on their chemical structure. Four software tools, Vega Hub, Toxtree, Lazar, and TEST, are used to predict the potential genotoxic and carcinogenic effects of the herbicides. Vega Hub uses QSAR models, Toxtree uses a decision tree approach, Lazar uses data mining algorithms, and TEST uses QSAR methods to estimate toxicity. The canonical Simplified Molecular Input Line Entry Specification (SMILES) systems of delachlor and xylachlor are entered into each software tool to create a prediction. The study found that delachlor and xylachlor is a class 3 highly toxic compounds with potential mutagenic and carcinogenic effects based on Toxtree and Vega Hub. Meanwhile, Lazar and TEST predicted that delachlor and xylachlor are unlikely to be mutagenic. This study to determine the toxicity of the herbicides delachlor and xylachlor has shown that the possible effects of these herbicides on health and the environment need to be further investigated. The results provide valuable insights into chloroacetanilide herbicide toxicity and help develop safer, more environmentally friendly alternatives.