Salvianolic acid derivatives-focused characterization in Salviae miltiorrhizae Radix et Rhizoma by LC×LC coupled with tandem energy-resolved mass spectrometry.

Salvianolic acid derivatives (SADs) represent a cluster of hydrosoluble phenolic acids and typically exist as monomer and oligomer forms in Salviae miltiorrhizae Radix et Rhizoma (Chinese name: Danshen). Because of the high-level structural similarity, even isomerism, it is technically challenging to achieve satisfactory separation and confidence-enhanced identification using conventional LC-MS/MS approaches. Here, an integrated strategy was proposed through simultaneously advancing LC separation, MS/MS information acquisition, and post-acquisition data processing. LC×LC was configured using HSS T3 and 5C18-AR-II columns for 1st and 2nd-dimensional separations, respectively, attributing to their sufficient complementary capabilities. By applying several data acquisition modes on the hybrid triple quadrupole-linear ion trap (QTRAP)-MS platform, including precursor ion scan, neutral loss scan, predictive multiple reaction monitoring, and step-wise multiple ion monitoring, a total of 143 SADs were captured. To facilitate structural identification, high-resolution mass values of all concerned SADs were obtained by LC-QTOF-MS. Meanwhile, a bottom-up structural annotation workflow was constructed by applying a tandem energy-resolved MS program. For signals-of-interest, the substructures were identified by matching full exciting energy ramp (FEER)-MS3 spectra with FEER-MSn (n = 2 or 3) spectra of known structures or fragments, and the linkage patterns amongst substructures were deciphered by incorporating full collision energy ramp (FCER)-MS2 spectra with quantum chemical calculation. As a result, confidence-enhanced structure identification was reached for 11 monomers, 19 dimers, 59 trimers, and 54 tetramers. Together, the strategy integrating LC×LC, diverse MS/MS modes, and bottom-up structural annotation enabled in-depth SADs-focused characterization in Danshen, providing a promising tool for chemical characterization of herbal medicines.