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Affinity-guided and activity-oriented consecutive-CCC/UNIFAC of acetylcholinesterase-binding ginsenosides from Black
Rui Meng1, Jingyi Han1, Yudi Li1
1Central Laboratory, Changchun Normal University, No. 677 North Chang-Ji Road, Changchun, 130032, China.
Abstract:
The preparative isolation of acetylcholinesterase (AChE)-binding ginsenosides from Black ginseng is challenged by matrix complexity, broad polarity distribution, and redundant solvent-phase preparation during repeated countercurrent chromatography (CCC). A crude extract prepared by RSM-GA-BP-guided UAE was evaluated by concentration-resolved UF-LC-MS at seven bovine-AChE concentrations, with enzyme-free and thermally inactivated-AChE controls used to distinguish system background and nonspecific protein-associated retention. Binding degree was used as the operational UF-LC-MS response, and weighted continuous piecewise regression was applied to describe pre- and post-transition response slopes; the slope-change coefficient (ΔS) provided the formal statistical test, whereas TSR was retained only as an empirical descriptive ratio. Experimental K-value screening selected ethyl acetate/n-butanol/water (1.0:3.0:5.0, v/v), and UNIFAC was used to calculate the upper- and lower-phase compositions required for direct preparation. Under the same CCC operating conditions, UNIFAC-assisted phase preparation produced target separation profiles comparable to conventional bulk phase preparation. Four consecutive CCC runs reduced fresh ethyl acetate and n-butanol preparation by 692 and 1976 mL, respectively (2668 mL total), while yielding seven fractions with chromatographic purities of 93.67-99.33%. HPLC and high-resolution mass spectrometry confirmed the isolated targets. All seven isolates showed reversible bovine-AChE inhibition, with IC50 values of 40.13, 40.63, 64.25, 41.13, 37.33, 29.52, and 30.02 μg/mL, respectively; Rg5 showed the highest inhibitory potency. Human-AChE docking, molecular dynamics, and MM/PBSA calculations were retained only as exploratory structural analyses. The evidence-integration matrix, network pharmacology, and machine-learning analyses were likewise treated only as exploratory components. These results establish a target-directed, solvent-efficient preparative chromatographic strategy that couples affinity prioritization with activity-oriented consecutive-CCC/UNIFAC for complex processed botanical matrices.