Development of a UHPLC-MS/MS-based data-mining method for rapid profiling and characterization of magnolol metabolites in rat urine and plasma

Abstract

Magnolol, an essential bioactive natural lignans isolated from Magnolia Officinalis, has various pharmacological activities, such as antibacterial, anti-inflammatory, antioxidation and anti-tumor. In this study, a practical strategy based on ultra-high-performance liquid chromatography coupled with linear ion trap-Orbitrap mass spectrometry (UHPLC-LTQ-Orbitrap MS) was established to reveal the metabolic fate of magnolol in rat plasma and urine. First of all, in the data-dependent scanning (DDS) acquisition mode, the ESI-MSn data sets of biological samples and reference standard were obtained by using a high-quality online data analysis method. Subsequently, off-line data-mining techniques including multiple mass defect filters (MMDFs) and high-resolution extracted ion chromatograms (HREICs) were applied to screen major-to-trace metabolites of magnolol at the full-scan ESI-MS1 level. Finally, a total of 177 metabolites (prototype compound included) were preliminarily observed and characterized according to accurate mass measurement, the characteristic fragmentation patterns, chromato-graphic behaviors, and corresponding Clog P values. The results showed that magnolol experienced a variety of biotransformation reactions in rats, including hydroxylation, methoxylation, dehydrogenation, carboxylation, sulfonation, glucuronide conjugation, glucose conjugation, N-acetylcysteine (NAC) conjugation, glutathione conjugation and their composite reactions. In conclusion, this study not only greatly expanded the understanding of the therapeutic material basis and pharmacological mechanism of magnolol, but also provided new ideas for its toxicity evaluation, safety monitoring and drug delivery forms design.

Keywords

• Magnolol
• UHPLC-LTQ-Orbitrap MS
• Data-mining techniques
• Metabolites