Pharmaceutics | 2021

Nontargeted Metabolomics by High-Resolution Mass Spectrometry to Study the In Vitro Metabolism of a Dual Inverse Agonist of Estrogen-Related Receptors β and γ, DN203368

 
 
 
 
 
 
 
 
 
 
 
 
 
 

Abstract


DN203368 ((E)-3-[1-(4-[4-isopropylpiperazine-1-yl]phenyl) 3-methyl-2-phenylbut-1-en-1-yl] phenol) is a 4-hydroxy tamoxifen analog that is a dual inverse agonist of estrogen-related receptor β/γ (ERRβ/γ). ERRγ is an orphan nuclear receptor that plays an important role in development and homeostasis and holds potential as a novel therapeutic target in metabolic diseases such as diabetes mellitus, obesity, and cancer. ERRβ is also one of the orphan nuclear receptors critical for many biological processes, such as development. We investigated the in vitro metabolism of DN203368 by conventional and metabolomic approaches using high-resolution mass spectrometry. The compound (100 μM) was incubated with rat and human liver microsomes in the presence of NADPH. In the metabolomic approach, the m/z value and retention time information obtained from the sample and heat-inactivated control group were statistically evaluated using principal component analysis and orthogonal partial least-squares discriminant analysis. Significant features responsible for group separation were then identified using tandem mass spectra. Seven metabolites of DN203368 were identified in rat liver microsomes and the metabolic pathways include hydroxylation (M1-3), N-oxidation (M4), N-deisopropylation (M5), N,N-dealkylation (M6), and oxidation and dehydrogenation (M7). Only five metabolites (M2, M3, and M5-M7) were detected in human liver microsomes. In the conventional approach using extracted ion monitoring for values of mass increase or decrease by known metabolic reactions, only five metabolites (M1-M5) were found in rat liver microsomes, whereas three metabolites (M2, M3, and M5) were found in human liver microsomes. This study revealed that nontargeted metabolomics combined with high-resolution mass spectrometry and multivariate analysis could be a more efficient tool for drug metabolite identification than the conventional approach. These results might also be useful for understanding the pharmacokinetics and metabolism of DN203368 in animals and humans.

Volume 13
Pages None
DOI 10.3390/pharmaceutics13060776
Language English
Journal Pharmaceutics

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