Compounds in cacti
Oxidation can lead to the production of unstable molecules called free radicals, which initiate chain reactions that can damage or even kill cells. #Antioxidants can therefore have highly beneficial effects.
Antioxidants, as their name suggests, inhibit oxidation reactions. Oxidation can lead to the production of unstable molecules called free radicals, which initiate chain reactions that can damage or even kill cells. Antioxidants can therefore have highly beneficial effects. Thanks to their cell-protecting properties, foods that contain antioxidants are highly sought after. They have been found in a wide range of fruits and vegetables, but also – more surprisingly – in cacti, especially of the #Pereskia genus. These cacti don’t look much like the archetypal versions, they have lots of leaves and thin stems and more closely resemble plants like roses. Pereskia #bleo is among 17 species of Pereskia cacti, consumed as a vegetable as well as being used as a traditional #herbal medicine in Latin America and Asia. Its leaves have been used to treat diseases associated with inflammation, such as high blood pressure, diabetes and even #cancer. Supporting its medical use, analyses have shown that P. bleo contains several bioactive elements, including alkaloids, flavonoids, sterols, terpenoids and carotenoids. It is the combined activity of this complex mixture of compounds that determines its clinical effects. This means the traditional method of isolating compounds and measuring their activity does not accurately represent its bioactivity. To properly analyse herbal extracts, chromatographic analysis of the entire sample should be used. When used alongside mathematical modelling, this technique can identify the peaks (and thus the compounds) responsible for biological activity. However, the major systems used for analysis – NMR, GC-MS and HPLC-MS – are prohibitively expensive in developing countries, where herbal extracts are most widely used. A more affordable alternative is thin-layer chromatography, which separates components using a thin layer of gel coated on a piece of glass, metal or plastic. When combined with multivariate analysis, a statistical technique used to examine the relationships between variables and construct predictive models, it can identify the compounds responsible for bioactivity.
In a newly published study, a method of multivariate analysis (called partial least square, or PLS) was used alongside thin-layer chromatography to predict antioxidant activity, and identify the responsible compounds, in P. bleo. Leaves were collected from Malaysia, dried and then ground into a powder. A total of 24 samples were made, each containing 10 g of powdered leaves and extracted with different percentages of a methanol/water mixture.
First, the biological activity of the extracts was evaluated using an assay that measures the ability to remove free radicals. Next, the samples were analysed by thin-layer chromatography in the mobile phase. The procedure was optimised using the PRISMA method, which is especially useful when the structures and properties of the substances to be separated are not known. “Systematic optimisation of the mobile phase was conducted to maximise separation. Resolution that was not achieved by thin-layer chromatography could complemented by applying supervised multivariate analysis,” explain authors of the paper Sharif Khan, PhD student at Monash University in Australia and Dr Mohd Mokhlesur Rahman, Associate Professor at the International Islamic University Malaysia.
Next came statistical analysis. The chromatographic image was mathematically converted and analysed using an OPLS model – an adaptation of the PLS technique which is easier to interpret. The model was externally validated by introducing new and independent samples, confirming the predictive ability of the model.
An affordable alternative
Unaided, the researchers could not identify any significant relationships between antioxidant activity and chromatographic bands. However, OPLS was able to identify clear variations that correlated to bioactivity.
The OPLS-reconstructed image revealed the bands that contributed the most to antioxidant activity, represented via brightness. The brightest band was analysed by GC-MS to reveal the two major contributing components: glycerol (74% of total area) and amines (21% of total area). This proves that OPLS can accurately predict antioxidant activity based on a thin-layer chromatography image. It also led to characterisation, as Khan clarifies: “Using this simple and holistic method, we successfully identified the compounds responsible for the pharmacological effects of this herb.”
This study shows that TLC image analysis can be used to predict the antioxidant activity of a complex herbal extract, applied here to P. bleo. It presents a novel method for predicting antioxidant activity and rapidly measuring the bioactivity of complex mixtures. This affordable and rapid method for multi-compound bioactivity analysis enables prediction of bioactivity without the need for an assay, and could allow developing nations to perform chemical analysis of their own herbal medicines.
Biomed Chromatography, 2015, 29(12), 1826–1833, Multivariate analysis of PRISMA optimized TLC image for predicting antioxidant activity and identification of contributing compounds from Pereskia bleo.
Article by Ryan De Vooght-Johnson
#Source: Separations Now
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