Deciphering and investigating fragment mechanism of quinolones using multi-collision energy mass spectrometry and computational chemistry strategy

Abstract

Rationale: Quinolones show characteristic fragments in mass spectrometry (MS) analysis due to their common core structures, and energy-dependent differences among these fragments are generated through the same fragmentation pathway of different molecules. Computational chemistry, which provides quantitative results of molecule parameters, is helpful for investigating the mechanisms of chemistry.

Methods: MS/MS spectra of five quinolones, namely norfloxacin (NOR), enoxacin (ENO), enrofloxacin (ENR), gatifloxacin (GAT), and lomefloxacin (LOM), were acquired for deciphering fragmentation pathways under multi-collision energy (CE). Computational methods were used for excluding little possibility pathways from the point of view of energy and stable conformations, whereas optimized collision energy (OCE) and maximum relative intensity (MRI) of major competitive fragments were investigated and confirmed using computational results.

Results: Fragmentation results of NOR, ENO, ENR, and GAT were deciphered using experimental and computational data, of which fragmentation regularities were summarized. Fragmentation pathways of LOM were deciphered under the guidance of foregoing regularities. Meanwhile, the whole process was validated by comparing OCE and MRI and computational energy results, which showed good agreement.

Conclusions: A strategy for explaining quinolone fragmentation results of multi-CE values and deciphering fragment mechanism using computational methods was developed. Relevant data and strategy may provide ideas for how to design and decipher new drug molecules with similar structures.