Optimization of extraction techniques and RP-HPLC analysis of anti-parkinson drug levodopa from flowers of Vicia faba L.

Abstract

Vicia faba, also known as “bakla” in Turkey, is a species of Fabaceae family that is widely grown in Africa and Asia. It is rich in levodopa, a medicinal substance used to treat Parkinson's disease. Levodopa produced by chemical synthesis is expensive and causes various side effects. Therefore, it is recommended to use natural levodopa sources to prevent possible side effects. A Central Composite Design technique has been used in this study to optimize levodopa extraction from Vicia faba. First, a single factor analysis examined 3 variables such as extraction temperature, extraction time, and concentration of acetic acid. The purpose of this study was to assess the effects of variables chosen on levodopa's extraction performance. By using variance and regression analyses, a second-order regression equation was determined as a predicted model. The value of R2 is 0.9882, which shows that the equation fits well. The best conditions are as follows: a temperature of 59.85 °C, an extraction time of 18.74 min, and an acetic acid content of 0.28%. Under optimum conditions, the maximum levodopa yield calculated from the predicted module was 4.53%. Extraction efficiency was determined as 4.54% experimentally under optimum conditions. A good relationship has been found between the experimental result and the predicted value.