Metabolic Profiling of Metoprolol via HPLC Coupled with ESI - QqQLIT Mass Spectrometry
Year: 2025
Type: article
Abstract: Metoprolol, a selective β₁-adrenergic antagonist, is widely prescribed for the treatment of hypertension and heart failure due to its proven mortality benefits. With the expected rise in cardiovascular diseases, understanding the metabolic fate of metoprolol is crucial for assessing its safety, efficacy, and pharmacokinetics. This study aimed to elucidate the in vitro metabolic pathways of metoprolol using High-Performance Liquid Chromatography coupled with Electrospray Ionization and hybrid Triple Quadrupole–Linear Ion Trap Mass Spectrometry (HPLC-ESI-QqQLIT-MS). Metabolism was simulated using in vitro systems, and metabolite identification was achieved through analysis of fragmentation patterns. The fragmentation pathway of metoprolol was first determined using Enhanced Product Ion (EPI) and MS³ spectra, supported by high-resolution mass spectrometry (HRMS) data. Subsequent identification of unknown metabolites relied on comparison with the parent drug’s fragmentation pattern, assuming structural similarity leads to analogous fragmentation behavior. Precursor Ion Scans (PI) and Neutral Loss Scans (NL), along with Data-Dependent Acquisition (DDA), enabled targeted detection and structural reconstruction of metabolites. A total of 29 product ions were identified in the collision-induced dissociation (CID) pathway of metoprolol. From these, 27 structures were proposed, revealing typical neutral losses of water, ammonia, propylene, and methanol. Identified metabolites included O-demethylmetoprolol (TP 1, m/z 254), three isomers of α-hydroxymetoprolol (TP 2a–2c, m/z 284), and metoprolol acid (TP 3, m/z 268). The findings demonstrate that HPLC-ESI-QqQLIT-MS, in combination with precursor and neutral loss scanning, is a robust and efficient technique for metabolite profiling and structural elucidation.
Source: Technium BioChemMed
Authors: Krenaida Taraj Lulja, Mary Mrad - Hage
Language: English
Subfield: Pharmacology
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4409795462