ABSTRACT
To investigate the metabolic rate and metabolites of 9-dehydro-17-dehydro-andrographolide, which is the main active ingredient in Xiyanping injection, by using the in vitro rat liver microsome incubation system. 9-dehydro-17-dehydro-andrographolide was incubated together with liver microsome mixed with NADPH. Its metabolic rate was studied by determining its residual concentrations with the UHPLC-MS/MS method; Its metabolites were identified by the UPLC-TOF-MS(E) method. The results showed that 9-dehydro-17-dehydro-andrographolide was metabolized faster than rat liver microsomes mixed with coenzymes, with t½ and CL of (19.7 ± 0.5) min and (35.1 ± 0.8) mL x min(-1) x g(-1) (protein), respectively. Based on the high resolution mass spectrum data and information from literatures, altogether nine metabolites of 9-dehydro-17-dehydro-andrographolide were identified in the incubation system, particularly hydroxylated and dehydrogenized products. The results of identification would provide a basis for screening out more active andrographolide derivatives.
Subject(s)
Animals , Rats , Chromatography, High Pressure Liquid , Diterpenes , Chemistry , Metabolism , Drugs, Chinese Herbal , Chemistry , Metabolism , Microsomes, Liver , Chemistry , Metabolism , Molecular Structure , Tandem Mass SpectrometryABSTRACT
This study is to establish the HPLC fingerprint and determine eight components of Callicarpa nudiflora, and provide a scientific basis for the identification and quality control. The Waters sunfire C18 column (4.6 mm x 250 mm, 5 µm) was used and the detection wavelength was 330 nm . The column temperature was 30 °C. The mobile phases were acetonitrile (A) and 0.1% formic acid (B) eluting in a gradient program at a flow rate of 1.0 mL · min(-1). The chromatographic fingerprint similarity evaluation system for tradition Chinese medicine(2012) was used for analysis. C. nudiflora from different samples were of high similarity in fingerprint and the separation of ten components was good. There was an obvious difference between other samples and C. nudiflora leaves. In quantitative analysis, the ten components showed good regression(R2 > 0 999 0) with linear ranges, and their recoveries were in the range of 96.0%-105.0%. The established qualitative and quantitative methods are highly specific, simple and accurate, which can be used for the identification and quality control of C. nudiflora.