Abstract

In this paper, a new strategy of drug metabolite discovery and identification was established using high-performance liquid chromatography with high resolution mass spectrometry (HPLC–HRMS) and a mass spectral trees similarity filter (MTSF) technique. The MTSF technique was developed as a means to rapidly discover comprehensive metabolites from multiple active components in a complicated biological matrix. Using full-scan mass spectra as the stem and data-dependent subsequent stage mass spectra to form branches, the HRMS and multiple-stage mass spectrometric data from detected compounds were converted to mass spectral trees data. Potential metabolites were discovered based on the similarity between their mass spectral trees and that known compounds or metabolites in a mass spectra trees library. The threshold value for match similarity scores was set at above 200, allowing approximately 80% of interference to be filtered out. A total of 115 metabolites of five flavonoid monomers (epimedin A, epimedin B, epimedin C, icariin, and baohuoside I) and herbal extract of epimedium were discovered and identified in rats via this new strategy. As a result, a metabolic profile for epimedium was obtained and a metabolic pathway was proposed. In addition, comparing to the widely used neutral loss filter (NLF), product ion filter (PIF), and mass defect filter (MDF) techniques, the MTSF technique was shown superior efficiency and selectivity for discovering and identifying metabolites in traditional Chinese medicine (TCM).

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