Objective To establish a method for differentiating gelatinous Chinese medicines (GCMs) based on supramolecular sensing technology. Methods An indicator displacement assay (IDA) strategy was employed where test sample solutions of GCMs served as analytes and macrocyclic molecule-dye host-guest pairs with specific fluorescence signals were used as sensing pairs to construct a sensor array. The fluorescence intensity changes resulting from the interaction between different GCMs and the sensing units were detected and combined with pattern recognition methods for differentiation. Results Through screening host-guest sensing units with selective fluorescence responses to GCMs from a supramolecular library consisting of cyclodextrins, cucurbiturils, calixarenes, and biphen[n]arenes hosts combined with dyes, a quaternary supramolecular sensor array was constructed including quaternary ammonium salt calix[5]arene (QAC5A)·eosin Y (EY) (0.4 μmol/L vs 0.5 μmol/L), quaternary ammonium modified azocalix[4]arene (QAAC4A)·EY (1 μmol/L vs 1 μmol/L), dodecyl quaternary ammonium salt azo calix[4]arene (QAAC4A12C)·EY (0.6 μmol/L vs 1 μmol/L), and terphen[3]arene (WTP3)·fluorescein (Fl) (0.3 μmol/L vs 0.6 μmol/L). Principal component analysis (PCA) demonstrated that Ejiao (Colla Corii Asini), Xin’ejiao (Colla Corii Suilli), Biejiajiao (Colla Carapacis Trionychis), Lugujiao (Colla Ossis Cervi), Guijiajiao (Colla Carapacis et Plastri Testudinis) or Lujiajiao (Colla Cornus Cervi) could be significantly distinguished within a 95% confidence interval. Conclusion This study developed a quaternary supramolecular sensor array integrated with pattern recognition analysis which enables rapid discrimination of various GCMs.

gelatinous traditional Chinese medicine  /  supramolecular sensing  /  indicator displacement assay  /  sensor array  /  differentiation  /  principal component analysis  /  Colla Corii Asini  /  Colla Corii Suilli  /  Colla Carapacis Trionychis  /  Colla Ossis Cervi  /  Colla Carapacis et Plastri Testudinis  /  Colla Cornus Cervi