Dose-independent ADME properties and tentative identification of metabolites of α-mangostin from Garcinia mangostana in mice by automated microsampling and UPLC-MS/MS methods

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Abstract

The information about a marker compound's pharmacokinetics in herbal products including the characteristics of absorption, distribution, metabolism, excretion (ADME) is closely related to the efficacy/toxicity. Also dose range and administration route are critical factors to determine the ADME profiles. Since the supply of a sufficient amount of a marker compound in in vivo study is still difficult, pharmacokinetic investigations which overcome the limit of blood collection in mice are desirable. Thus, we have attempted to investigate concurrently the ADME and proposed metabolite identification of α-mangostin, a major constituent of mangosteen, Garcinia mangostana L, in mice with a wide dose range using an in vitro as well as in vivo automated micro-sampling system together. α-mangostin showed dose-proportional pharmacokinetics at intravenous doses of 5-20 mg/kg and oral doses of 10-100 mg/kg. The gastrointestinal absorption of α-mangostin was poor and the distribution of α-mangostin was relatively high in the liver, intestine, kidney, fat, and lung. α-mangostin was extensively metabolized in the liver and intestine. With regards to the formation of metabolites, the glucuronidated, bis-glucuronidated, dehydrogenated, hydrogenated, oxidized, and methylated α-mangostins were tentatively identified. We suggest that these dose-independent pharmacokinetic characteristics of α-mangostin in mice provide an important basis for preclinical applications of α-mangostin as well as mangosteen. In addition, these experimental methods can be applied to evaluate the pharmacokinetics of natural products in mice.

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Han, S. Y., You, B. H., Kim, Y. C., Chin, Y. W., & Choi, Y. H. (2015). Dose-independent ADME properties and tentative identification of metabolites of α-mangostin from Garcinia mangostana in mice by automated microsampling and UPLC-MS/MS methods. PLoS ONE, 10(7). https://doi.org/10.1371/journal.pone.0131587

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