Rapid detection and structural characterization of verapamil metabolites in rats by UPLC-MSE and UNIFI platform.

High-resolution mass spectrometry (HRMS) is an important technology for studying biotransformations of drugs in biological systems. In order to process complex HRMS data, bioinformatics, including data-mining techniques for identifying drug metabolites from liquid chromatography/high-resolution mass spectrometry (LC/HRMS) or multistage mass spectrometry (MSn ) datasets as well as elucidating the detected metabolites’ structure by spectral interpretation software, are important tools. Data-mining technologies have widely been used in drug metabolite identification, including mass defect filters, product ion filters, neutral-loss filters, control sample comparisons and extracted ion chromatographic analysis. However, the metabolites identified by current different technologies are not the same, indicating the importance of technique integration for efficient and complete identification of metabolic products. In this study, a universal, high-throughput workflow for identifying and verifying metabolites by applying the drug metabolite identification software UNIFI is reported, to study the biotransformation of verapamil in rats. A total of 71 verapamil metabolites were found in rat plasma, urine and faeces, including two metabolites that have not been reported in the literature. Phase I metabolites of verapamil were identified as N-demethylation, O-demethylation, N-dealkylation and oxidation and dehydrogenation metabolites; phase II metabolites were mainly glucuronidation and sulfate conjugates, indicating that UNIFI software could be effective and valuable in identifying drug metabolites

Identifying potential anti-COVID-19 pharmacological components of traditional Chinese medicine Lianhuaqingwen capsule based on human exposure and ACE2 biochromatography screening

药学院吴彩胜副教授联合海军军医大学柴逸峰教授团队在连花清瘟胶囊防治新冠肺炎的药理活性成分和机制研究方面取得新进展，这项研究基于HRMS和智能非靶向数据挖掘技术，全面分析了对多次给药后人血浆和尿液中的连花清瘟胶囊成分，合成了全新的ACE2生物色谱固定相，筛选出连花清瘟胶囊提取物和人尿液样品潜在的ACE2靶向成分。这项研究是连花清瘟胶囊的人体暴露信息的首次报道，为其在抗COVID-19的药理活性成分和作用机制研究提供了化学和药理学理论依据。本研究证明基于人体暴露的研究策略可用于高效的发掘中草药中的药效活性物质。【Abstract】Lianhuaqingwen (LHQW) capsule, a herb medicine product, has been clinically proved to be effective in coronavirus disease 2019 (COVID-19) pneumonia treatment. However, human exposure to LHQW components and their pharmacological effects remain largely unknown. Hence, this study aimed to determine human exposure to LHQW components and their anti-COVID-19 pharmacological activities. Analysis of LHQW component profiles in human plasma and urine after repeated therapeutic dosing was conducted using a combination of HRMS and an untargeted data-mining approach, leading to detection of 132 LHQW prototype and metabolite components, which were absorbed via the gastrointestinal tract and formed via biotransformation in human, respectively. Together with data from screening by comprehensive 2D angiotensin-converting enzyme 2 (ACE2) biochromatography, 8 components in LHQW that were exposed to human and had potential ACE2 targeting ability were identified for further pharmacodynamic evaluation. Results show that rhein, forsythoside A, forsythoside I, neochlorogenic acid and its isomers exhibited high inhibitory effect on ACE2. For the first time, this study provides chemical and biochemical evidence for exploring molecular mechanisms of therapeutic effects of LHQW capsule for the treatment of COVID-19 patients based on the components exposed to human. It also demonstrates the utility of the human exposure-based approach to identify pharmaceutically active components in Chinese herb medicines.The authors would like to thank Prof. Chuan Li in Shanghai Institute of Materia Medica, Chinese Academy of Sciences (Shanghai, China) to provide biological samples and technical guidance. This research was supported by Natural Science Foundation of China, China, (Grant Nos. 81773688, U1903119, 81973291, and 81973275); Zhejiang University Special Scientific Research Fund for COVID-19 Prevention and Control, China; “Phospherus” Project of Shanghai Science and Technology Committee, China, (Grant Nos. 19QA1411500); National Major Scientific and Technological Special Project for "Significant New Drugs Development", China, (Grant No. 2020ZX09201005)

Removal of Sulfur from Coal Using Mild Oxidizing Conditions

Methods for the determination of organic sulfur in coal and for the identification of organic sulfur compounds in coal and coal extracts are reviewed. Most studies have focused on the thiophenic sulfur groups in coal which are the most stable and the most difficult to remove. The goal of this research was to optimize mild oxidizing conditions capable of removing inorganic and aliphatic sulfur constituents from coal, but not thiophenic sulfur groups. Consequently, mild oxidizing conditions were used to quantify the amounts of aliphatic sulfur compounds in Illinois Basin coals and the distribution of these compounds in different ranks of coals. The results of this research indicated the optimum mild oxidizing conditions are aqueous slurries of 5% coal ( 60 mesh) in 1 M NH4OH reacted at 7 - 10 atm of O2 and 150 - 200°C for 1.5 hrs. Under these conditions 22 - 44% of the organic sulfur, 81 - 95% of the inorganic sulfur, and 51 - 75% of the total sulfur are removed from Illinois Basin Coals. In addition, it appears that aliphatic sulfur is higher in high sulfur coals than in low sulfur coals, and is very low in high rank anthracite coal. Aliphatic sulfur in the Illinois Basin bituminous coals studied ranged from 22% to 44%

High-Throughput Metabolic Soft-Spot Identification in Liver Microsomes by LC/UV/MS: Application of a Single Variable Incubation Time Approach

CYP-mediated fast metabolism may lead to poor bioavailability, fast drug clearance and significant drug interaction. Thus, metabolic stability screening in human liver microsomes (HLM) followed by metabolic soft-spot identification (MSSID) is routinely conducted in drug discovery. Liver microsomal incubations of testing compounds with fixed single or multiple incubation time(s) and quantitative and qualitative analysis of metabolites using high-resolution mass spectrometry are routinely employed in MSSID assays. The major objective of this study was to develop and validate a simple, effective, and high-throughput assay for determining metabolic soft-spots of testing compounds in liver microsomes using a single variable incubation time and LC/UV/MS. Model compounds (verapamil, dextromethorphan, buspirone, mirtazapine, saquinavir, midazolam, amodiaquine) were incubated at 3 or 5 µM with HLM for a single variable incubation time between 1 and 60 min based on predetermined metabolic stability data. As a result, disappearances of the parents were around 20–40%, and only one or a few primary metabolites were generated as major metabolite(s) without notable formation of secondary metabolites. The unique metabolite profiles generated from the optimal incubation conditions enabled LC/UV to perform direct quantitative estimation for identifying major metabolites. Consequently, structural characterization by LC/MS focused on one or a few major primary metabolite(s) rather than many metabolites including secondary metabolites. Furthermore, generic data-dependent acquisition methods were utilized to enable Q-TOF and Qtrap to continuously record full MS and MS/MS spectral data of major metabolites for post-acquisition data-mining and interpretation. Results from analyzing metabolic soft-spots of the seven model compounds demonstrated that the novel MSSID assay can substantially simplify metabolic soft-spot identification and is well suited for high-throughput analysis in lead optimization