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Dissecting parameters contributing to the underprediction of aldehyde oxidase-mediated metabolic clearance of drugs .

Sandhya SubashDilip K SinghDeepak S AhireS Cyrus KhojastehBernard P MurrayMichael A ZientekRobert S JonesPriyanka KulkarniBill J SmithScott HeywardCiaran N CroninBhagwat Prasad
Published in: Drug metabolism and disposition: the biological fate of chemicals (2023)
We investigated the effect of variability and instability in aldehyde oxidase (AO) content and activity on scaling of in vitro metabolism data. AO content and activity in human liver cytosol (HLC) and five recombinant human AO preparations (rAO) were determined using targeted proteomics and carbazeran oxidation assay, respectively. AO content was highly variable as indicated by the relative expression factor (REF, i.e., HLC to rAO content) ranging from 0.001-1.7 across different in vitro systems. The activity of AO in HLC degrades at a 10-fold higher rate in the presence of the substrate as compared to the activity performed after preincubation without substrate. To scale the metabolic activity from rAO to HLC, a protein-normalized activity factor (pnAF) was proposed wherein the activity was corrected by AO content, which revealed upto 6-fold higher AO activity in HLC versus rAO systems. A similar value of pnAF was observed for another substrate, ripasudil. Physiologically-based pharmacokinetic (PBPK) modeling revealed a significant additional clearance (CL; 66%), which allowed successful prediction of in vivo CL of four other substrates, i.e., O-benzyl guanine, BIBX1382, zaleplon and zoniporide. For carbazeran, the metabolite identification study showed that the direct glucuronidation may be contributing to around 12% elimination. Taken together, this study identified differential protein content, instability of in vitro activity, role of additional AO clearance and unaccounted metabolic pathways as plausible reasons for the underprediction of AO mediated drug metabolism. Consideration of these factors and integration of REF and pnAF in PBPK models will allow better prediction of AO metabolism. Significance Statement We elucidated the plausible reasons for the underprediction of aldehyde oxidase (AO) mediated drug metabolism and provided recommendations to address them. We demonstrated that integrating protein content and activity differences, accounting for the loss of AO activity, as well as consideration of extrahepatic clearance and additional pathways would improve the in vitro to in vivo extrapolation of AO mediated drug metabolism using physiologically-based pharmacokinetic modeling.
Keyphrases
  • mass spectrometry
  • small molecule
  • machine learning
  • high throughput
  • high resolution
  • single molecule
  • big data
  • atomic force microscopy