Quantification of Bioactive Compounds in Mentat Tablet (MT)

Quantification of Bioactive Compounds in Mentat Tablet (MT) An ultra-performance liquid chromatography electrospray ionization tandem mass spectrometry method has been developed and validated for simultaneous quantification of twenty-eight major bioactive compounds in Mentat tablet (MT), a complex Indian herbal medicine used in the treatment of neurological disorder and improvement of mental health. Multiple-reaction monitoring scanning was employed for quantification in positive and negative mode. The analysis was accomplished on Waters AQUITY UPLC BEH C18 column with linear gradient elution of water/formic acid (0.1%) and acetonitrile/formic acid (0.1%) at a flow rate of 0.3 mL/min. The proposed method was validated with acceptable linearity (r2, 0.9984-0.9999), precision (RSD, 0.22–2.11%), stability (RSD, 0.16–1.78%) and recovery (RSD ≠¤ 3.74 %), under optimum conditions. The limits of quantitation were low ranging from 0.28 to 3.88 ng/mL for the 28 compounds. The method was successfully applied to the simultaneous deter mination of 28 compounds in twenty batches of MT tablets. Also, hierarchical cluster analysis and principle component analysis was applied to categorize 20 samples based on characteristics of the 28 bioactive compounds. The results have indicated that this advanced method is rapid, sensitive and suitable to show the real quality of the MT composition and also capable of controlling quality of polyherbal formulations having similar markers/raw herbs. Keywords: Multiple Reaction Monitoring / Multi-Marker Quantification / UPLC-ESI-MS/MS / Hierarchical Cluster Analysis / Principle Component Analysis 1. Introduction Herbal medicines (HMs) refer to one herb or complex mixtures, which usually contains hundreds of chemically different components. Their curative effects are principally based on the synergic effect of their multi-targeting and multi-ingredient preparations [1, 2]. Consequently, quality control becomes troublesome for crude drugs. the method that employs pharmacologically active components to evaluate the quality and authenticity of the complex preparations is confronted with severe challenges. Therefore, better analytical strategies to assure their efficacy, safety, and consistency is essential and in great demand [3]. Moreover, the chemical compounds in the poly herbs in HMs products may vary depending on harvest seasons, plant origins, drying processes and other factors. Thus, it seems to be necessary to determine most of the phytochemical constituents of herbal products in order to ensure the reliability and repeatability of pharmacological and clinical research and to enhance pro duct quality control [4, 5]. Currently, selection of a single or a few specific components from a certain herbal medicine as markers for quality assessment is a widely applied strategy. However, it cannot afford sufficient quantitative information for the other medicinal compositions and cannot accurately reflect the quality of HMs products. All the HMs compositions play important roles in the therapeutic effects. Therefore, selecting multiple constituents from different medicinal herbs as evaluation markers has been gradually applied for the quality control of HMs [6, 7]. Mentat tablets (MT, commercial product) is a polyherbal medication with each tablet composed of multiple herbs extracts (listed in Table S1). Major contributed herbs are Bacopa monnieri, Centella asiaticaand Withania somnifera. MT is a unique all-natural multi-ingredient formula that promotes brain health. It improves the mental quotient, memory span, concentration ability, stress threshold and exhibit significant anti-parkinsonian activity. MT also offers protection against convulsions, which is beneficial in insomnia with its sedative and tranquilizing effects [8-10]. Chemically bacosides, saponin mixture in B. monnieri, triterpenoid glycosides in C. asiatica, steroidal lactones in W. somnifera are the major representative ingredients in MT, in comparison to others. [11-14]. Phytochemical investigations show important classes of bioactive constituents in selected plants which are as in combination of MT that are responsible for the bioactivity [15-20]. Literature survey reveals various analytical methods including thin layer chromatography (TLC) [21], high performance thin layer chromatography (HPTLC) [22, 23], liquid chromatography (LC) [6, 24, 25], liquid chromatography coupled with mass spectrometry (LC-MS) [26-29], nuclear magnetic resonance (NMR) [30] for the quantitative analysis of the bioactive constituents in HMs to assess the quality of the complex preparations. To the best of our knowledge, there is no method reported for the simultaneous estimation of selected 28 multi-markers in herbals by UPLC-ESI-MS/MSand no such approach has been explored on this important drug combination for quality and consistency evaluation of this herbal preparation. Natural alteration in preparation processes and climate affects the safety and batch-to-batch uniformity of HMs products. Highly sensitive analytical methods are thus required to identify ingredients and evaluate batch-to-batch variation. Compared to conventional TLC, HPTLC, HPLC method which are less sensitive and takes longer analysis time, UPLC-ESI-MS/MS method in multiple reaction monitoring (MRM) mode is more powerful approach. Due to its rapid separation power, low detection limit, high sensitivity, selectivity and specificity, UPLC-ESI-MS/MS offers effective detection to quantify multi-ingredients in complex sample matrices. Previous methods reported in literature only contained one or few compounds, without the consideration of other active ingredients. This paper describes for the first time a simple, accurate and reliable UPLC-ESI-MS/MS method for the simultaneous determination of 28 multiple bioactive compounds from different polyherbs viz., bacoside A (mixture of bacoside A3, bacopaside II, bacopaside X and bacopasaponin C), withanolide-A, withaferin-A, asiaticoside, madecassoside, jatrorrhizine, palmatine, magnoflorine, curcumin, gallic acid, protocatechuic acid, ferulic acid, caffeic acid, ellagic acid, rosamarinic acid, ursolic acid, catechin, apigenin, luteolin, quercetin, rutin, kaempferol-3-O-rutinoside, corilagin, chrysin and chlorogenic acid with single runtime of 10 min. This method is intended not only for quality control of commercial polyherbal formulated products but also for efficient evaluation of raw materials. The quantitative results were further analyzed by multivariate statistical analysis i.e., hierarchical cluster analysis (HCA) and principle component analysis (PCA) to provide more information about the ch emical differences and batch-to-batch variations. Chemical Structures of all analytes and internal standards were showed in Fig 1. 2. Experimental 2.1 Reagents and materials The reference standards (purity≠¥90%) bacoside A (mixture of bacoside A3, bacopaside II, bacopaside X and bacopasaponin C) was purchased from Natural Remedies Pvt. Ltd. Apigenin, kaempferol-3-O-rutinoside, protocatechuic acid, rosamarinic acid, caffeic acid, ferulic acid, ursolic acid, palmatine, withanolide-A, withaferin-A, asiaticoside, madecassoside, jatrorrhizine, magnoflorine, catechin, chlorogenic acid, curcumin, rutin, corilagin, chrysin, gallic acid and ellagic acid were purchased from Sigma Aldrich Ltd. (St. Louis, MO, USA). Reference standards of quercetin, luteolin and internal standards (IS) andrographolide and piperine were purchased from Extrasyntheses (Genay, France). Twenty different batches of Mentat tablets produced by Himalaya Drug Company, Bangalore, India were purchased from local drug stores from different places in India (Table S2). For all solutions and dilutions, methanol, acetonitrile (LC-MS grade) and formic acid (analytical grade) were purchased from Fluka, Sigma–Aldrich (St. Louis, MO, USA). Milli-Q Ultra-pure water was obtained from a Millipore water purification system (Millipore, Milford, MA, USA). 2.2 Preparation of standard solutions and samples A stock solution containing 28 standards i.e., bacoside A (mixture of bacoside A3, bacopaside II, bacopaside X and bacopasaponin C), withanolide-A, withaferin-A, asiaticoside, madecassoside, jatrorrhizine, palmatine, magnoflorine, curcumin, gallic acid, procatechuic acid, ferulic acid, caeffic acid, ellagic acid, rosamaric acid, ursolic acid, catechin, apigenin, luteolin, quercetin, rutin, kaempferol-3-O-rutinoside, corilagin, chrysin and chlorogenic acid were weighed accurately, dissolved in pure methanol.The working standard solutions were prepared by diluting the mixed standard solution with methanol to a series of concentrations within the ranges from 1 to 1000 ng/mL used for plotting the calibration curves. Meanwhile, each standard was also prepared respectively. The coating of each samples were removed completely, and the remains were smashed into powder. Pulverized sample (0.5g) was weighed precisely, and sonicated by ultrasonicator (53 KHz, Bandelin SONOREX, Berlin) using 50 ml 100% methanol at room temperature for 30 min. The extracted solution was centrifuged at 15000 rpm for 10 min, and the supernatant was filtered through a 0.22  µm syringe filter (Millex-GV, PVDF, Merck Millipore, Darmstadt, Germany) to obtained 10,000  µg/ml. The à ¯Ã‚ ¬Ã‚ ltrates were diluted with methanol to final working solutions and analyzed directly by UPLC-ESI-MS/MS. The internal standards andrographolide for negative mode and piperine for positive mode were spiked to each working concentration of mixed standards solution and sample solution at a final concentration of 50 ng/mL (50  µL of internal standards mixture of 1000 ng/mL of each in methanol) were mixed properly. All solutions were stored at -200C until use and sonicated prior to injection. 2.3 Instrumentation and analytical conditions An Acquity ultra-performance liquid chromatography (UPLCTM) system consisting of an auto sampler and a binary pump (Waters, Milford, MA was used for analysis. The compounds were separated on an Acquity BEH C18 (2.1 mmÃâ€" 50 mm, 1.7 µm; Waters, Milford, MA) analytical column at a column temperature of 25à ¢- ¦C. A gradient elution was achieved using two solvents: 0.1% (v/v) formic acid in water (A) and 0.1% (v/v) formic acid in acetonitrile (B) at a flow rate of 0.3 mL/min. The gradient program consisted of an initial of 5% with linear increase from 5% to 60% B over 1.85 to 7.5 min and increased from 60% B to 90% B over 8.5 min, which was maintained for 1.5 min, followed by a return to the initial condition over 2.5 min with a sample injection volume of 5 µL. The UPLC system was interfaced with hybrid linear ion trap triple-quadrupole mass spectrometer (API 4000 QTRAPâ„ ¢ MS/MS system from AB Sciex, Concord, ON, Canada) equipped with electrospray (Turbo V) ion source. The optimized parameters for positive mode were as follows: the ion spray voltage was set to 5500 V; the turbo spray temperature, 550à ¢- ¦C; nebulizer gas (gas 1), 50 psi; heater gas (gas 2), 50 psi; collision gas, medium; the curtain gas (CUR) was kept at 20 psi. Optimized parameter for negative mode were as follows: the ion spray voltage was set to −4200 V, the turbo spray temperature, 550à ¢- ¦C; nebulizer gas (gas 1), 20 psi; heater gas (gas 2), 20 psi; collision gas, medium; the curtain gas (CUR) was kept at 20 psi. Quantitative analysis was performed using multiple-reaction monitoring (MRM) mode and its conditions were optimized for each compound during infusion. For full scan ESI-MS analysis, the spectra covered the range from m/z 100 to 1000. Analyst 1.5.1 software package (AB Sciex) used for instrument control and data acquisition. The results of the precursor ion, product ion, corresponding declustering potential (DP), entrance potential (EP), collision energy (CE), cell exit potential (CXP) were shown in Table S3. 2.4 Multivariate analysis Hierarchical cluster analysis (HCA) is a tool to identify relatively homogeneous groups of cases based on selected characteristics, using an algorithm that starts with each case in a separate cluster until only one is left. In the experiment, HCA of 20 batches of samples were performed, in which a method called average linkage between groups was employed and 28 markers were selected as the measurement. Similarly, Principal component analysis (PCA) was carried out based on the contents of quantified 28 bioactive compounds in 20 batches of samples. All the experiment was done using software STATISTICA 7.0. When the contents of investigated compounds were below the quantitation limit or not detected in the samples, the values of such elements were considered to be zero.