Integrated Multiplatform Analysis and Separation of Thirteen Flavonoids and Anthraquinones in Seven Medicinal Cassia Species.

Abstract

Cassia (Family: Fabaceae) species are a large group of flowering plants rich in bioactive anthraquinone and flavonoids used in botanical supplements and nutraceuticals. A simple and reliable high-performance liquid chromatography-photodiode array (HPLC-PDA) method was developed and validated for separating and quantifying thirteen anthraquinone and flavonoids. These compounds were further confirmed using an LC-based electrospray ionization mass spectrometry (ESI-MS/MS) method in the leaves and flowers of selected Cassia species. A simple and rapid HPTLC method was developed for chemical fingerprint analysis of all Cassia species. All thirteen compounds were chromatographically separated on a Zorbax TC18 (4.6 x 250, 5 μm particle size) analytical column, and 0.1% formic acid and acetonitrile as elution solvents at a flow rate of 0.8 mL/min with detection at 259 nm. For HPTLC fingerprinting, the mobile phase compositions of toluene, ethyl acetate, and formic acid (5.5:4.2:0.6, v/v/v) were optimized to separate and identify all compounds using silica gel 60F254 aluminum plates. The validation data for the developed HPLC-PDA method for thirteen compounds showed good linearity (r2 > 0.99) with a sensitive LOD (0.082-1.969 mg/mL), LOQ (0.250-5.967 mg/mL), and excellent recoveries (85.22-100.32%). The quantification results were found to be precise and accurate (<5.0% and relative error), -0.77-0.44 with ESI-MS/MS confirmation in the Cassia samples. The novel HPTLC method was excellent separation for thirteen compounds, with Rf values ranging between 0.12- 0.61. The developed HPLC-PDA method was simple, and precise and could separate and quantify anthraquinones and flavonoids along with confirmation, using a novel LC-based ESI-MS/MS. The HPTLC method was found to be simple and precise, with excellent separation capabilities for these compounds. This novel multiplatform approach successfully identified and quantified thirteen compounds simultaneously using an integration of data strategy in seven medicinally important Cassia species' leaves and flowers.