predicting chemical toxicity in rivers near electricity station outlet discharges using quantitative structure-activity relationship (qsar)

In this study, chemical toxicity prediction was conducted using in silico approaches due to their importance for human health and environmental concerns. analysis of tigris river samples near a power station outlet revealed ten compounds, with three identified as toxic by in silico tools. toxtree software classified three compounds as high hazards, including heavy aromatic naphtha, light aromatic naphtha, and naphthalene, which was corroborated by qsar database analysis. qsar data indicated positive ames tests for eight naphtha derivatives, suggesting their mutagenic potential. molecular docking demonstrated strong binding affinity (-6.6 kcal/mol) between naphtha and cytochrome p450, crucial for xenobiotic metabolism, indicating potential interference with detoxification processes. this study highlights the utility of in silico methods in identifying and assessing environmental chemical hazards, emphasizing the importance of monitoring and mitigating toxic pollutants. further investigation into the long-term environmental impact and bioaccumulation potential of these identified toxic compounds is warranted to ensure comprehensive risk assessment and management.