Chromatographic method development and metabolite profiling for biomass and extraction optimization of withametelin and daturaolone from D. Innoxia Mill.

Abstract

Low yields of isolated natural compounds halt the drug discovery process as they can only be used for structure elucidation studies and basic biological screening. Metabolite profiling via chromatographic means for optimized selection of biomass and extraction medium can help resolve the issue. In line with this, the project is focused on metabolite profiling of Datura innoxia regarding its two bioactive principals i.e., withametelin and daturaolone. Samples (8 4 0) were prepared via collection of five parts (leaves, stem, fruit, root, flowers) from two geographically different regions of Pakistan i.e., Islamabad and Muzaffargarh for six months (May-October) and extraction in fourteen solvent systems of varied polarity range, respectively. Six months agroclimatology data (temperature, humidity, soil wetness, UV irradiance) was also obtained. TLC co-detection method (n-hexane: ethyl acetate; 7:3) of withametelin and daturaolone was developed and analysis was performed on all samples. RP HPLC method was developed for withametelin (Linearity = R 2 ;0.9) and daturaolone (linearity: R 2 ;0.9) and 118 samples which showed detections in TLC analysis were quantified. Withametelin was mostly detected in leaves with a maximum quantified value of 5.12 ± 0.28 µg/mg dry plant powder when collected in June from arid Muzaffargarh region and extracted with Ethyl acetate + Ethanol (1:1). Distribution of daturaolone is mostly found in fruits with a maximum quantified value of 5.18 ± 0.45 µg/mg dry plant powder when collected in August from mountainous Islamabad region and extracted with Ethyl acetate + Ethanol (1:1). The study states that the presence and quantitative variations of withametelin and daturaolone depend on the plant’s part, extraction medium, geographical location, weather conditions and soil wetness. Use of a controlled environment research to determine the quantitative relationship between different parameters is proposed.