atractylenolide-ii and ferulic-acid

We developed a simultaneous analysis method using high-performance liquid chromatography coupled with diode-array detector (HPLC-DAD) for six principal compounds (atractylenolide III, alisol A, alisol B, paeoniflorin, ferulic acid and (Z)-ligustilide) in a traditional Japanese (Kampo) medicine, tokishakuyakusan (TSS). The HPLC separation was conducted on a reversed-phase TSK-gel ODS-80TS column (4.6 i.d. × 250 mm, 5 µm) at 40°C with a 0.1% phosphoric acid-acetonitrile gradient system. The DAD detection wavelength was set at 205, 232 and 330 nm. Calibration curves for the compounds showed linear regressions with correlation coefficients of >0.999. The intra- and inter-day precision (i.e., the relative standard deviation) were in the range of 0.50-1.55 and 0.70-1.80%, respectively. The average recovery yields of the compounds ranged from 98.3 to 103%. The present results will contribute to shorter analysis times with less organic solvent compared with the individual analysis of each compound for the evaluation of TSS. The application of the established method to TSS will also provide helpful information for the further pharmacological and clinical studies.

Topics: 4-Butyrolactone; Cholestenones; Chromatography, High Pressure Liquid; Coumaric Acids; Drugs, Chinese Herbal; Glucosides; Lactones; Limit of Detection; Linear Models; Monoterpenes; Reproducibility of Results; Sesquiterpenes

The present study aims to predict the action targets of antidepressant active ingredients of Xiaoyaosan to understand the "multi-components, multi-targets and multi-pathways" mechanism. Using network pharmacology, the reported antidepressant active ingredients in Xiaoyaosan (saikosaponin A, saikosaponin C, saikosaponin D, ferulic acid, Z-ligustilide, atractylenolide I, atractylenolide II, atractylenolide III, paeoniflorin, albiflorin, liquiritin, glycyrrhizic acid and pachymic acid), were used to predict the targets of main active ingredients of Xiaoyaosan according to reversed pharmacophore matching method. The prediction was made via screening of the antidepressive drug targets approved by FDA in the DrugBank database and annotating the information of targets with the aid of MAS 3.0 biological molecular function software. The Cytoscape software was used to construct the Xiaoyaosan ingredients-targets-pathways network. The network analysis indicates that the active ingredients in Xiaoyaosan involve 25 targets in the energy metabolism-immune-signal transmutation relevant biological processes. The antidepressant effect of Xiaoyaosan reflects the features of traditional Chinese medicine in multi-components, multi-targets and multi-pathways. This research provides a scientific basis for elucidation of the antidepressant pharmacological mechanism of Xiaoyaosan.

Topics: Antidepressive Agents; Benzoates; Bridged-Ring Compounds; Coumaric Acids; Drug Evaluation, Preclinical; Drugs, Chinese Herbal; Flavanones; Glucosides; Glycyrrhizic Acid; Lactones; Medicine, Chinese Traditional; Monoterpenes; Sesquiterpenes; Software