Predicting Chemical-Gene Interactions

Abstract: Pesticide use in agriculture has become a growing concern as it can have detrimental effects on the environment. The excessive use of these chemicals often leads to them seeping into nearby water bodies, causing harm to aquatic organisms. Recent studies have shown that these compounds can even alter the genetic makeup of these organisms, which can have farreaching consequences. In this study, pesticide data from two agriculture sites, Skivarpsån and Skåne M42, were analysed to predict the effects of pesticides on a selected aquatic organism. The data for this study was collected from various sources, including the National Centre for Biotechnology Information, the STITCH database, and the PubChem database. The STITCH chemical-protein interaction prediction model provided a careful analysis of the chemical compounds and their interaction with genes. The main result of this study shows that between the two sites, M42 is highly polluted with a greater number of chemicals detected than the Skivarpsån site. Furthermore, this study indicates that higher protein-gene interactions are expected in M42 compared to the Skivarpsån site. The stream with significant pesticide mixture pollution will have more interactions between small molecules and proteins than streams with low pesticide loads. The function enrichment on both sides shows that the chemicals that have the highest effect on the organisms are insecticides affecting their biological aspects. Despite the usefulness of these resources, one of the limitations of the study was that several nodes remained undetermined.