Biased cytochrome P450-mediated metabolism via small-molecule ligands binding P450 oxidoreductase

Metabolic control is mediated by the dynamic assemblies and function of multiple redox enzymes. A key element in these assemblies, the P450 oxidoreductase (POR), donates electrons and selectively activates numerous (>50 in humans and >300 in plants) cytochromes P450 (CYPs) controlling metabolism of drugs, steroids and xenobiotics in humans and natural product biosynthesis in plants. The mechanisms underlying POR-mediated CYP metabolism remain poorly understood and to date no ligand binding has been described to regulate the specificity of POR. Here, using a combination of computational modeling and functional assays, we identify ligands that dock on POR and bias its specificity towards CYP redox partners, across mammal and plant kingdom. Single molecule FRET studies reveal ligand binding to alter POR conformational sampling, which results in biased activation of metabolic cascades in whole cell assays. We propose the model of biased metabolism, a mechanism akin to biased signaling of GPCRs, where ligand binding on POR stabilizes different conformational states that are linked to distinct metabolic outcomes. Biased metabolism may allow designing pathway-specific therapeutics or personalized food suppressing undesired, disease-related, metabolic pathways. P450 oxidoreductase (POR) selectively activates numerous cytochromes P450 (CYP), crucial for metabolism of drugs, steroids and xenobiotics and natural product biosynthesis. Here, the authors identify ligands that bind POR and bias its specificity towards CYP redox partners, activating distinct metabolic cascades in cells.

Automated summary

This study identifies ligands that bind to P450 oxidoreductase (POR) and bias its specificity towards cytochromes P450 (CYP) redox partners, activating distinct metabolic cascades in cells. Single molecule FRET studies reveal that ligand binding alters the conformational sampling of POR, leading to biased activation of metabolic pathways in whole cells. This biased metabolism model may hold potential for designing pathway-specific therapeutics or personalized food to suppress unwanted, disease-related metabolic pathways.