COMPUTATIONAL DOCKING STUDIES OF NITROANISOLES WITH CYP2E1

这个子项目是众多研究子项目之一

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Microsomal P450s (P450 or CYP for a particular isoform) oxidize a structurally diverse class of compounds including steroids, fatty acids, antibiotics, and a wide variety of foreign, biologically active (xenobiotic) chemicals, such as drugs, food additives, and environmental contaminants. In vitro kinetic profiling of P450 reactions provides an important tool for elucidating the biological role of P450 activity. The strategy provides valuable parameters that describe the specificity and efficiency of P450-catalyzed reactions. Knowledge of the significance and consequence of P450 metabolism facilitates drug design, food safety guidelines, and environmental regulations regarding exposure to pollutants, and thus accurate modeling of P450 reactions is critical. Though hyperbolic kinetic profiles are typical, a growing number of P450 reactions demonstrate non-hyperbolic kinetic profiles. These results do not conform to the Michaelis-Menten model used for traditional hyperbolic kinetic profiles, and instead require more complex mechanisms. Despite significant efforts to study the activity of those P450s, little is known about non-hyperbolic reactions observed for CYP2E1. Nitroanisoles are members of class of potent toxic and carcinogenic compounds, presenting a considerable danger to the human population. These pollutants are widely distributed in workplaces, especially dye industries, and the environment due to emissions from diesel and gasoline engines, ambient air particulate matter, and toxic spills. Significant efforts have identified products and the corresponding P450s responsible for nitroanisole detoxification; however, the kinetic profiles that describe the flux of these compounds to inactive metabolites require investigation. We will generate computational models of liganded complexes through two different docking approaches to identify the stoichiometry complexes and corresponding contact residues for bound ligands. These models, combined with biophysical and biochemical data, will allow us to determine the structure-function relationships for CYP2E1 relevant to the detoxification of carcinogenic nitroanisoles.