Metabolite identification of the antimalarial piperaquine in vivo using liquid chromatography-high-resolution mass spectrometry in combination with multiple data-mining tools in tandem

Artemisinin‐based combination therapy is widely used for the treatment of uncomplicated Plasmodium falciparum malaria, and piperaquine (PQ) is one of important partner drugs. The pharmacokinetics of PQ is characterized by a low clearance and a large volume of distribution; however, metabolism of PQ...

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Bibliographic Details
Published in:Biomedical chromatography 2016-08, Vol.30 (8), p.1324-1330
Main Authors: Yang, Aijuan, Zang, Meitong, Liu, Huixiang, Fan, Peihong, Xing, Jie
Format: Article
Language:English
Subjects:
Animals
Antimalarials - blood
Antimalarials - metabolism
Antimalarials - urine
Chromatography, Liquid - methods
Humans
isotope pattern filter
liquid chromatography tandem high-resolution mass spectrometry
mass defect filter
metabolites
piperaquine
Plasmodium falciparum
Quinolines - blood
Quinolines - metabolism
Quinolines - urine
Rats
Tandem Mass Spectrometry - methods
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Summary:Artemisinin‐based combination therapy is widely used for the treatment of uncomplicated Plasmodium falciparum malaria, and piperaquine (PQ) is one of important partner drugs. The pharmacokinetics of PQ is characterized by a low clearance and a large volume of distribution; however, metabolism of PQ has not been thoroughly investigated. In this work, the metabolite profiling of PQ in human and rat was studied using liquid chromatography tandem high‐resolution LTQ‐Orbitrap mass spectrometry (HRMS). The biological samples were pretreated by solid‐phase extraction. Data processes were carried out using multiple data‐mining techniques in tandem, i.e., isotope pattern filter followed by mass defect filter. A total of six metabolites (M1–M6) were identified for PQ in human (plasma and urine) and rat (plasma, urine and bile). Three reported metabolites were also found in this study, which included N‐oxidation (M1, M2) and carboxylic products (M3). The subsequent N‐oxidation of M3 resulted in a new metabolite M4 detected in urine and bile samples. A new metabolic pathway N‐dealkylation was found for PQ in human and rat, leading to two new metabolites (M5 and M6). This study demonstrated that LC‐HRMSn in combination with multiple data‐mining techniques in tandem can be a valuable analytical strategy for rapid metabolite profiling of drugs. Copyright © 2016 John Wiley & Sons, Ltd.
ISSN:0269-3879
1099-0801
DOI:10.1002/bmc.3689