Exploring the quality marker of Curcumae kwangsiensis radix from different production regions using the spectrum-effect relationship, serum metabolism, and molecular docking integrated with chemometrics

Abstract

Ethnopharmacological relevance

Curcuma kwangsiensis radix (CKR) is one of the most important herbs in traditional Chinese medicine. It effectively enhances blood circulation and eliminates stasis, which is highly associated with thrombosis. Furthermore, CKR is primarily produced in the Guangxi and Yunnan provinces of China. However, the quality control indicators of CKR in different production regions remain controversial.

Aim

To explore the quality marker (Q-Marker) of CKR in different production regions.

Materials and methods

First, we determined the UPLC fingerprints of CKR from different production regions. Second, in vitro, antiplatelet aggregation biopotency (AAB) was measured using a parallel-line assay based on the quantitative response method of the bioassay. We identified CKR components and their serum metabolism using UPLC-Q-TOF-MS^E. Subsequently, molecular docking technology was used for Q-Marker analysis. Finally, we established a method for the quantitative analysis of Q-Marker.

Results

We observed significant differences of CKR between the Guangxi and Yunnan provinces according to the UPLC fingerprint and AAB results. Eight quality control-relevant components were screened using orthogonal partial least squares based on the spectrum-effect relationship. UPLC-Q-TOF-MS^E identified 57 CKR components, and 10 prototype components and 11 metabolites, respectively, were detected during serum metabolism. Ultimately, curcumenone was screened as a Q-Marker using the spectrum-effect relationship integrated with serum metabolism, which positively correlated with the quality. The AAB results of the Q-Marker indicated that curcumenone exhibited significant anti-platelet aggregation activity. The results of the Q-Marker molecular docking revealed the strongest binding effect between curcumenone and the GP-IIb/IIIa receptor, whereas that between the P2Y12 receptor and the P2Y1 receptor was the weakest. In addition, quantitative analysis of the Q-Marker indicated that there were significant differences in the contents of the Q-Marker from different production regions.

Conclusions

We identified a Q-Marker for CKR that can provide a foundation for quality evaluation research from different production regions.