Targeted Submetabolome Profiling of Bufadienolides in Venenum Bufonis Using Scheduled Diagnostic Product Ion–Pair Filtering and Substructure Recognition‐Based Strategy

ABSTRACT Introduction Venenum bufonis (VB), a traditional animal‐derived medicine, exhibits significant antitumor, immunomodulatory, and analgesic activities that are primarily attributed to bufadienolides. Objective This study presented a novel targeted submetabolomics strategy for comprehensive profiling of bufadienolides in VB. Material and Methods This targeted submetabolome mainly integrated scheduled diagnostic product ion (DPI) pair–based filtering and substructure recognition‐based structural assembly based on the LC–MS platform. Key steps included 1) stepwise multiple ion monitoring (MIM) coupled with a dynamic exclusion function to enhance detection of minor peaks; 2) automated annotation of unconjugated bufadienolides via high‐resolution extracted ion chromatograms (EICs) and a Microsoft Excel‐based platform; 3) establishment of an extended tail database for conjugated bufadienolides (including dicarboxylic acid and dicarboxylic acid–amino acid conjugates) based on structural similarity and derivativity, enabling untargeted screening via validated or scheduled DPI pairs derived from MS/MS fragmentation patterns; and 4) potential conjugated bufadienolides were characterized via a substructure recognition‐based strategy. Results The strategy identified 162 bufadienolides (39 primary, 39 secondary, and 84 tertiary) with a 96% annotation rate (155 characterized). Notably, 81 potential novel compounds were discovered, including 11 previously undescribed structural subclasses. Conclusions This targeted submetabolome strategy significantly expanded the diversity of bufadienolides in VB and also advanced the application of mass spectrometry in natural product discovery.