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

Abstract

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.

Direct Observation of Heterogeneous Formation of Amyloid Spherulites in Real-time by Super-resolution Microscopy

“…To extract growth rate kinetics for each individual aggregate, we identified points belonging to the growing aggregate with an approximate Euclidean Minimum Spanning tree segmentation 38 and estimated the area using a gaussian mixture model, based on hierarchical clustering in Fig. 3c and 3d (see Supplementary information for the details) [23][24][25][26] . For isotropic morphologies a single linear growth rate is observed (rx), while for anisotropic morphologies the growth curve consists of two rate components (r1 and r2), as shown in Fig.…”

“…Consistent with the 3D dSTORM data, the direct observation of HI spherulite growth by REPLOM confirmed that HI spherulites grow both anisotropically and isotropically (Figure 3). To extract the growth rate kinetics for each individual aggregate, we identified the points belonging to the growing aggregate with an approximate Euclidean Minimum Spanning tree segmentation (Cowan & Ivezić, 2008) and estimated the area using a Gaussian mixture model based on hierarchical clustering in Figure 3c and 3d (see Supporting Information for the details) (Jensen et al, 2021; Pinholt et al, 2021; Stella et al, 2018; J. Thomsen et al, 2020).…”

“…We developed a method for the detection of Real-time kinetics via binding and Photobleaching Localisation Microscopy ( REPLOM ) to attain real-time videos of the spherulite growth process and reconstruct super-resolution images of the spherulites and their growth kinetics. Using homemade software based on Euclidian minimum spanning tree and machine learning clustering (Jensen et al, 2021; Malle et al, 2021; Pinholt, Bohr, Iversen, Boomsma, & Hatzakis, 2021; Stella et al, 2018; J. Thomsen et al, 2020), we quantitatively associated the growth rates to specific morphological transitions during growth, eventually extracting detailed energy barriers and, thus, the energy landscape for each type of aggregation morphology.…”

“…We developed a method for the detection of REal-time kinetics via binding and Photobleaching LOcalization Microscopy (REPLOM), to attain real-time video of spherulites growth process, reconstruct the super-resolution image of the spherulites and their growth kinetics. Using home-made software based on Euclidian minimum spanning tree and machine learning clustering [23][24][25][26] , we quantitatively associated growth rates to specific morphological transitions during the growth, eventually extracting detailed energy barriers and thus the energy landscape for each morphology type of the aggregation. These findings underscore how conclusions solely based on bulk kinetics data may overlook the complexity and the heterogeneity of the aggregation process.…”

Transcript profiles of wild and domesticated sorghum under water-stressed conditions and the differential impact on dhurrin metabolism

“…Then CYP71E1 catalyses the conversion of the oxime into the cyanohydrin p -hydroxymandelonitrile (Bak et al 1998 ) which upon glycosylation, catalysed by UGT85B1, is converted into dhurrin (Jones et al 1999 ). In these processes, the NADPH-dependent cytochrome P450 oxidoreductase (POR) serves as an obligatory electron donor to the two P450s (Jensen et al 2021 ; Halkier and Møller 1991 ) and is localized in the endoplasmic reticulum forming an enzyme complex (metabolon) with CYP79A1 and CYP71E1 that recruits the UGT85B1 (Laursen et al 2015 ; Jensen et al 2011 ; Nielsen et al 2008 ). The formation of a metabolon prevents the escape of toxic intermediates.…”