A computational approach to mechanistic and predictive toxicology of pesticides

Abstract

Emerging challenges of managing and interpreting large amounts of complex biological data have given rise to the growing field of computational biology. We investigated the applicability of an integrated systems toxicology approach on five selected pesticides to get an overview of their modes of action in humans, to group them according to their modes of action, and to hypothesize on their potential effects on human health.
We extracted human proteins associated with prochloraz, tebuconazole, epoxiconazole, procymidone, and mancozeb and enriched each protein set by using a high confidence human protein interactome. Then we explored modes of action of the chemicals by integrating protein-disease information into the resulting protein networks. The dominating resulting human adverse effects were reproductive disorders followed by adrenal diseases.
Our results indicated that prochloraz, tebuconazole, and procymidone exert their effects mainly via interference with steroidogenesis and nuclear receptors. Prochloraz was associated with a large number of human diseases and, together with tebuconazole, showed several significant associations with testicular dysgenesis syndrome. Mancozeb showed a differential mode of action involving inflammatory processes.
This method provides an efficient way of overviewing data and grouping chemicals according to their mode of action and potential human adverse effects. Such information is valuable when dealing with predictions of mixture effects of chemicals and may contribute to the development of adverse outcome pathways.