Identification of novel pyrimidine ring cleavage metabolites of Buspirone via Spectral Similarity correlation score

Importance of the Topic

Comprehensive characterization of drug metabolism is essential for understanding pharmacokinetics, safety profiles, and potential bioactivation pathways. Buspirone, an anxiolytic agent of the azapirone class, undergoes complex biotransformation in human liver microsomes. Identifying unexpected metabolites advances our knowledge of xenobiotic clearance and informs risk assessment in drug development.

Objectives and Study Overview

This study leveraged a non-targeted Spectral Similarity Correlation scoring approach to detect novel pyrimidine ring cleavage products of Buspirone. By comparing MSn fragment and neutral loss patterns between unknown chromatographic peaks and the parent drug, the method aimed to reveal metabolites without prior assumptions about cleavage sites.

Methodology and Instrumentation

• Sample Incubation: Buspirone (30 μM) incubated with human liver microsomes and NADPH at 37 °C for 45 minutes.
• Liquid Chromatography: Shimadzu LCMS IT-TOF system equipped with a 2.1×50 mm C18 BEH 1.7 μm column. Mobile phases: A) water + 0.1% formic acid; B) acetonitrile + 0.1% formic acid. Gradient from 2% B to 90% B over 9 minutes at 0.6 mL/min and 65 °C.
• Mass Spectrometry: Data-dependent MSn acquisition on an IT-TOF analyzer to capture MS2 and MS3 spectra.
• Data Analysis: MetID Solutions v1.2 software generated Spectral Similarity (S) Scores by correlating fragment ions and neutral losses of unknown peaks against the Buspirone MSn reference.

Key Results and Discussion

• Initial non-targeted screening identified 47 peaks with positive S Scores; comparison with known Phase I metabolites narrowed candidates to 12 unknowns.
• Two peaks at m/z 350.2531 (2.45 min) and m/z 438.2707 (2.31 min) exhibited key fragment ions (222, 265, 291 m/z) matching Buspirone, indicative of pyrimidine ring cleavage.
• MS3 analysis of the 438 m/z precursor showed a fragment spectrum identical to the standalone 350 m/z metabolite, supporting a sequential cleavage pathway.

Benefits and Practical Applications

• An unbiased workflow requiring no a priori knowledge of specific metabolic transformations.
• Reduction of candidate elemental formulas through fragment similarity, streamlining structural elucidation.
• Compatibility with automated metabolite identification pipelines in pharmaceutical research and quality control.

Future Trends and Applications

• Integration with in silico metabolism predictions and machine learning to enhance detection sensitivity.
• Application to a broader range of drug classes and complex biological matrices.
• Optimization of scoring thresholds and expansion of spectral libraries for more comprehensive non-targeted screening.

Conclusion

The Spectral Similarity Correlation approach enabled discovery of previously unreported pyrimidine ring cleavage metabolites of Buspirone in a non-targeted human microsomal system. This strategy offers a powerful tool for unbiased metabolite profiling in drug metabolism studies.

Reference

1. Prakash A. & Cui D. Drug Metabolism & Disposition. 1997;25(12):1395–1406.
2. Zhu J. et al. Drug Metabolism & Disposition. 2005;33(4):500–507.