Chemical Fingerprint Analysis and Quantitative Analysis of Saccharides in Morindae Officinalis Radix by HPLC-ELSD

A method based on high performance liquid chromatography with evaporative light scattering detection (HPLC-ELSD) was developed for the quantitative analysis of three active compounds and chemical fingerprint analyses of saccharides in Morindae officinalis radix. Ten batches of Morindae officinalis radix were collected from different plantations in the Guangdong region of China and used to establish the fingerprint. The samples were separated with a COSMOIL Sugar-D column (4.6 mm × 250 mm, 5 μm) by using gradient elution with water (A) and acetonitrile (B). In addition, Trapped-Ion-Mobility (tims) Time-Of-Flight (tims TOF) was used to identify saccharides of Morindae officinalis radix. Fingerprint chromatogram presented 26 common characteristic peaks in the roots of Morinda officinalis How, and the similarities were more than 0.926. In quantitative analysis, the three compounds showed good regression (r = 0.9995–0.9998) within the test ranges, and the recoveries of the method were in the range of 96.7–101.7%. The contents of sucrose, kestose and nystose in all samples were determined as 1.21–7.92%, 1.02–3.37%, and 2.38–6.55%, respectively. The developed HPLC fingerprint method is reliable and was validated for the quality control and identification of Morindae officinalis radix and can be successfully used to assess the quality of Morindae officinalis radix.

Chemical Fingerprint Using FTIR and HPLC as Qualitative Analysis in the Study of Propagation of Labisia pumila Var. Alata

Labisia pumila, known as kacip fatimah is a traditional herbs widely used for women. The herb was used as a post partum medicine to help contract the birth channel. From previous research, 120 clones of Labisia pumila var. alata was collected from three different locations and 30 clones of the herbs was found having high yielding of total phenolic content (TPC). In this study, one clone from each location was selected for further analyses, which are TA14 from Kuala Berang, TSA13 from Kemaman and DA20 from Gua Musang. Fourier Transform Infrared spectroscopy (FTIR) associated with second derivative infrared spectroscopy was applied to identify the chemical fingerprint of each clone of Labisia pumila. This analytical method is highly rapid and effective for analysis of medicinal herbs. Second derivative IR spectroscopy could enhance the spectral resolution by amplifying tiny differences in the IR spectrum. In this method, the whole chemical property of the sample can be revealed and shown in the IR spectrum. A total of ten absorption peaks were obviously present in the IR spectra which can be used to characterize the species. The IR spectra shows the presence of broader peak at frequencies of range 3266 – 3338 cm-1 which attributable to the alcohol group. This study also attempts to develop HPLC fingerprint of the selected clones. Observation on HPLC spectra shows the presence of one distinct peak at retention time of 12.30, 12.99 and 12.93 min, respectively in each clone. This compound will be characterized and will be used as reference compound in quality assessment in plant breeding

Novel Antibiotics from a ‘White Box’ 2D Structural Fingerprint Decision Tree

<p>The paper is concerned with repurposing drugs based on chemical similarity to existing drugs, with an application to antibiotics. A simple ‘white box’ 2D chemical fingerprint-based decision tree approach is shown to largely recapitulate a neural network study in the literature. In particular, the repurposing of halicin is shown to be based on an explicit fingerprint pattern, unlike the neural network ‘black box’ methodology.</p>

Novel Antibiotics from a ‘White Box’ 2D Structural Fingerprint Decision Tree

<p>The paper is concerned with repurposing drugs based on chemical similarity to existing drugs, with an application to antibiotics. A simple ‘white box’ 2D chemical fingerprint-based decision tree approach is shown to largely recapitulate a neural network study in the literature. In particular, the repurposing of halicin is shown to be based on an explicit fingerprint pattern, unlike the neural network ‘black box’ methodology.</p>

Phytochemical Profiling and Quality Control of Terminalia sericea Burch. ex DC. Using HPTLC Metabolomics

Terminalia sericea is used throughout Africa for the treatment of a variety of conditions and has been identified as a potential commercial plant. The study was aimed at establishing a high-performance thin layer chromatography (HPTLC) chemical fingerprint for T. sericea root bark as a reference for quality control and exploring chemical variation within the species using HPTLC metabo3lomics. Forty-two root bark samples were collected from ten populations in South Africa and extracted with dichloromethane: methanol (1:1). An HPTLC method was optimized to resolve the major compounds from other sample components. Dichloromethane: ethyl acetate: methanol: formic acid (90:10:30:1) was used as the developing solvent and the plates were visualized using 10% sulfuric acid in methanol as derivatizing agent. The concentrations of three major bioactive compounds, sericic acid, sericoside and resveratrol-3-O-β-rutinoside, in the extracts were determined using a validated ultra-performance liquid chromatography-photodiode array (UPLC-PDA) detection method. The rTLC software (written in the R-programming language) was used to select the most informative retardation factor (Rf) ranges from the images of the analysed sample extracts. Further chemometric models, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), were constructed using the web-based high throughput metabolomic software. The rTLC chemometric models were compared with the models previously obtained from ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS). A characteristic fingerprint containing clear bands for the three bioactive compounds was established. All three bioactive compounds were present in all the samples, although their corresponding band intensities varied. The intensities correlated with the UPLC-PDA results, in that samples containing a high concentration of a particular compound, displayed a more intense band. Chemometric analysis using HCA revealed two chemotypes, and the subsequent construction of a loadings plot indicated that sericic acid and sericoside were responsible for the chemotypic variation; with sericoside concentrated in Chemotype 1, while sericic acid was more abundant in Chemotype 2. A characteristic chemical fingerprint with clearly distinguishable features was established for T. sericea root bark that can be used for species authentication, and to select samples with high concentrations of a particular marker compound(s). Different chemotypes, potentially differing in their therapeutic potency towards a particular target, could be distinguished. The models revealed the three analytes as biomarkers, corresponding to results reported for UPLC-MS profiling and thereby indicating that HPTLC is a suitable technique for the quality control of T. sericea root bark.