Formation and Biological Targets of Quinones: Cytotoxic versus Cytoprotective Effects.

Quinones represent a class of toxicological intermediates, which can create a variety of hazardous effects in vivo including, acute cytotoxicity, immunotoxicity, and carcinogenesis. In contrast, quinones can induce cytoprotection through the induction of detoxification enzymes, anti-inflammatory activities, and modification of redox status. The mechanisms by which quinones cause these effects can be quite complex. The various biological targets of quinones depend on their rate and site of formation and their reactivity. Quinones are formed through a variety of mechanisms from simple oxidation of catechols/hydroquinones catalyzed by a variety of oxidative enzymes and metal ions to more complex mechanisms involving initial P450-catalyzed hydroxylation reactions followed by two-electron oxidation. Quinones are Michael acceptors, and modification of cellular processes could occur through alkylation of crucial cellular proteins and/or DNA. Alternatively, quinones are highly redox active molecules which can redox cycle with their semiquinone radical anions leading to the formation of reactive oxygen species (ROS) including superoxide, hydrogen peroxide, and ultimately the hydroxyl radical. Production of ROS can alter redox balance within cells through the formation of oxidized cellular macromolecules including lipids, proteins, and DNA. This perspective explores the varied biological targets of quinones including GSH, NADPH, protein sulfhydryls [heat shock proteins, P450s, cyclooxygenase-2 (COX-2), glutathione S-transferase (GST), NAD(P)H:quinone oxidoreductase 1, (NQO1), kelch-like ECH-associated protein 1 (Keap1), IκB kinase (IKK), and arylhydrocarbon receptor (AhR)], and DNA. The evidence strongly suggests that the numerous mechanisms of quinone modulations (i.e., alkylation versus oxidative stress) can be correlated with the known pathology/cytoprotection of the parent compound(s) that is best described by an inverse U-shaped dose-response curve.