Enhanced metabolite profiling of herbal products using an integrated 4-in-1 analysis system and the MetaboTarget algorithm.

The inherent chemodiversity and complexity of herbal products make their quality control extremely challenging. In this work, a comprehensive analysis strategy through combining a polarity-extended liquid chromatography-mass spectrometry system (4-in-1 analysis system) and a metabolite-oriented targeted screening algorithm (MetaboTarget) for herbal products was proposed. The 4-in-1 analytical technique significantly expanded detection coverage of analytes through polarity extension. The Python-based MetaboTarget algorithm constructs a predictive database of potential metabolites by integrating Phase I/II metabolic reaction rules with parent drug components absorbed into the blood. Using precursor ions for targeted DDA scanning of plasma samples enables comprehensive metabolite characterization through integration with feature-based molecular networking (FBMN). The developed strategy was successfully applied to the deep in vitro and in vivo analysis of chemical components of Gegen Qinlian Decoction (GQD). As a result, 303 components in GQD and 181 metabolites in plasma were annotated. This integrated strategy enables simultaneous detection of compounds across the full polarity spectrum (high/medium/low) while overcoming key challenges in metabolite identification through the MetaboTarget algorithm, which effectively addresses issues arising from strong endogenous interference and low target abundance, thereby providing a powerful tool for comprehensive characterization of complex herbal products.