Orthogonality-driven offline two-dimensional liquid chromatography coupled with high-resolution mass spectrometry for comprehensive chemical profiling and quality marker screening of Renshen Guben oral liquid.

Traditional Chinese patent medicines present formidable analytical challenges due to their multi-herb composition, extreme polarity diversity, and vast concentration disparities among constituents, rendering conventional one-dimensional liquid chromatography-mass spectrometry (1D LC-MS) insufficient for comprehensive quality assessment. This study establishes an orthogonality-driven offline two-dimensional liquid chromatography system (HILIC × RPLC) coupled with Q-Orbitrap mass spectrometry for in-depth chemical profiling and rational quality marker (Q-marker) screening of Renshen Guben oral liquid (RSGB), a clinically used immunomodulatory formulation comprising ten herbal ingredients. The 2D-LC platform was systematically optimized and validated, achieving a ~50-fold improvement over 1D LC-MS in component coverage. Global natural products social molecular networking (GNPS) was employed to visualize MS/MS spectral similarity relationships, facilitating confident annotation of structurally related analogues across 13 chemical classes. A total of 260 compounds were identified, among which 48 were verified against reference standards. Building upon this comprehensive chemical foundation, a multidimensional Q-marker screening strategy was devised by integrating network pharmacology prediction, molecular docking evaluation against the core immune-related target HSP90AA1, and chromatographic fingerprint correlation of ten constituent herbs, ultimately designating 12 compounds from eight distinct herbs as Q-markers. To address the wide dynamic range in component abundance, an adjusted multiple reaction monitoring (MRM) method utilizing triple quadrupole mass spectrometry was developed, enabling simultaneous quantification spanning three orders of magnitude. Method validation demonstrated excellent linearity (R2 > 0.999) and satisfactory precision and repeatability for all 12 Q-markers. Quantitative analysis of ten commercial batches revealed significant inter-batch variations, with gallic acid as the most abundant constituent and alisol B the least, underscoring the necessity of multicomponent quality control. This integrated workflow bridges the gap between comprehensive chemical characterization and pragmatic quantitative assessment, offering a transferable paradigm for holistic quality evaluation of complex botanical formulations.