Prediction and Analysis of Quality Markers for Jianpi Antai Granules Based on Fingerprint Chromatography and Network Pharmacology

OBJECTIVE To provide a scientific basis for comprehensive quality control of Jianpi Antai granules through a multi-component fingerprint analysis of Jianpi Antai granules using high performance liquid chromatography(HPLC) and predict potential quality marker(Q-marker) through network pharmacology.

METHODS HPLC was employed to analyze the fingerprint of Jianpi Antai granules and predict its potential Q-markers. Concurrently, network pharmacology methods were utilized to predict the therapeutic targets of Jianpi Antai granules for spontaneous abortion, and molecular docking techniques were applied to evaluate the binding affinity between Q-markers and core targets.

RESULTS An HPLC fingerprint of Jianpi Antai granules was successfully established, identifying 7 major chromatographic peaks as Q-markers. Network pharmacology analysis predicted 128 therapeutic targets, involving crucial signaling pathways such as PI3K-Akt/Ras/MAPK. Molecular docking results revealed good binding affinity between Q-markers and key targets, with the lowest binding energy of −10.6 kcal·mol⁻¹ between hyperin and AKT1.

CONCLUSION The established HPLC fingerprint exhibits good stability and reproducibility, providing a reference for quality evaluation of Jianpi Antai granules. The potential Q-markers and their mechanisms of action are successfully predicted and validated through network pharmacology, providing a scientific basis for further research on their mechanisms of action.