Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools.

Data-independent acquisition (DIA) based strategies have been explored in recent years for improving quantitative analysis of metabolites. However, the data analysis is challenging for DIA methods as the resulting spectra are highly multiplexed. Thus, the DIA mode requires advanced software analysis to facilitate the data deconvolution process. We proposed a pipeline for quantitative profiling of pharmaceutical drugs and serum metabolites in DIA mode after comparing the results obtained from full-scan, Data-dependent acquisition (DDA) and DIA modes. using open-access software. Pharmaceutical drugs (10) were pooled in healthy human serum and analysed by LC-ESI-QTOF-MS. MS1 full-scan and Data-dependent (MS2) results were used for identification using MS-DIAL software while deconvolution of MS1/MS2 spectra in DIA mode was achieved by using Skyline software. The results of acquisition methods for quantitative analysis validated the remarkable analytical performance of the constructed workflow, proving it to be a sensitive and reproducible pipeline for biological complex fluids.

The LC-QTOF-MS/MS analysis of acid degradation products of Rifaximin, an antibiotic.

The present research aims to propose a simple and accurate technique for the analysis of Rifaximin in the presence of its stress degradation products and analysis of degradation products by LC-MS/MS analysis. Rifaximin was submitted to forced degradation under the acid hydrolysis condition as prescribed by the ICH. The extract was prepared by firstly treated with HCl and heated about 4 to 8 h. The filtrate was collected and separated using dichloromethane followed by evaporation in rotary evaporator to obtain a solid crude extract which was then stored under refrigeration at -80 °C. Liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS/MS) was utilized to identify products in the drug sample. The data processing results revealed the presence of 9 products in the degraded sample of Rifaximin. This data article contains the m/z [M + H +] values, molecular formula, retention times and the comprehensive list of m/z values detected during the LC- QTOF- MS/MS analysis.

Metabolite Profiling and Quantitation of Cucurbitacins in Cucurbitaceae Plants by Liquid Chromatography coupled to Tandem Mass Spectrometry.

Cucurbitaceae is an important plant family because many of its species are consumed as food, and used in herbal medicines, cosmetics, etc. It comprises annual vines and is rich in various bioactive principles which include the cucurbitacins. These steroidal natural products, derived from the triterpene cucurbitane, are mainly the bitter principles of the family Cucurbitaceae. Their biological activities include anti-inflammatory, hepatoprotective, and anti-cancer activities. A total of 10 species belonging to 6 genera of the Cucurbitaceae family along with Cissampelos pareira (Menispermaceae) were included in this study. A comprehensive profiling of certain natural products was developed using HPLC-QTOF-MS/MS analysis and a distribution profile of several major natural products in this family was obtained. A total of 51 natural products were detected in both positive and negative ionization modes, based on accurate masses and fragmentation patterns. Along with this, quantitation of four bioactive cucurbitacins, found in various important plants of the Cucurbitaceae family, was carried out using multiple reaction monitoring (MRM) approach on an ion trap mass spectrometer. Cucurbitacin Q was found to be the most abundant in C. pareira, while Citrullus colocynthis contained all four cucurbitacins in abundant quantities. The developed quantitation method is simple, rapid, and reproducible.

Combining untargeted and targeted metabolomics approaches for the standardization of polyherbal formulations through UPLC-MS/MS.

INTRODUCTION: Polyherbal formulations are an integral part of various indigenous medicinal systems such as Traditional Chinese Medicine (TCM) and Ayurveda. The presence of a very large number of compounds makes the quality control of polyherbal formulations very difficult. OBJECTIVES: To overcome this problem, we have developed a comprehensive strategy for the dereplication of natural products in polyherbal formulations by using Adhatoda vasica as a case study. METHODS: The strategy is based on five major steps: the collection of plant samples from different locations to observe the effects of environmental variables; LC-ESI-MS/MS-based untargeted metabolite profiling of the plant samples to identify marker compounds using extensive chemometric analysis of the obtained data; the identification of marker compounds in polyherbal products; the isolation, purification and characterization of the marker compounds; and MRM-based quantitative analysis of the isolated marker compounds using LC-ESI-MS/MS. RESULTS: Using this strategy, we identified a total of 51 compounds in the methanolic extract of A. vasica plants from 14 accessions. Chemical fingerprinting of the plant led to the identification of characteristic peaks that were used to confirm the presence of A. vasica in complex polyherbal formulations. Four quinazoline alkaloids (marker compounds) were isolated, purified and quantified in various herbal formulations containing A. vasica. CONCLUSION: This method demonstrates a comprehensive strategy based on untargeted and targeted metabolite analysis that can be used for the standardization of complex polyherbal formulations.