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  • Author: Tamam M. El-Elimat x
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In this study, high-performance liquid chromatography with fluorescence detection (HPLC-FLD) has been used for the first time, for direct determination of warfarin and its major metabolite, 7-hydroxywarfarin, in rat plasma. The simple and sensitive method was developed using Fortis® reversed-phase diphenyl column (150 × 4.6 mm, 3 μm) and a mobile phase composed of phosphate buffer (25 mmol L−1)/methanol/acetonitrile (70:20:10, V/V/V), adjusted to pH 7.4, at a flow rate of 0.8 mL min−1. The diphenyl chemistry of the stationary phase provided a unique selectivity for separating the structurally related aromatic analytes, warfarin and 7-hydroxywarfarin, allowing their successful quantification in the complex plasma matrix. The method was linear over the range 0.01–25 μg mL−1, for warfarin and 7-hydroxywarfarin, and was found to be accurate, precise and selective in accordance with US FDA guidance for bioanalytical method validation. The method was sensitive enough to quantify 0.01 μg mL−1 of warfarin and 7-hydroxywarfarin (LLOQ) using only 100 μL of plasma. The applicability of this method was demonstrated by analyzing samples obtained from rats after oral administration of a single warfarin dose, and studying warfarin and 7-hydroxywarfarin pharmacokinetics.


The glyoxalase system, particularly glyoxalase-I (GLO-I), has been approved as a potential target for cancer treatment. In this study, a set of structurally diverse polyphenolic natural compounds were investigated as potential GLO-I inhibitors. Ellagic acid was found, computationally and experimentally, to be the most potent GLO-I inhibitor among the tested compounds which showed an IC 50 of 0.71 mmol L−1. Its binding to the GLO-I active site seemed to be mainly driven by ionic interaction via its ionized hydroxyl groups with the central Zn ion and Lys156, along with other numerous hydrogen bonding and hydrophobic interactions. Due to its unique and rigid skeleton, it can be utilized to search for other novel and potent GLO-I inhibitors via computational approaches such as pharmacophore modeling and similarity search methods. Moreover, an inspection of the docked poses of the tested compounds showed that chlorogenic acid and dihydrocaffeic acid could be considered as lead compounds worthy of further optimization.