摘要
Here we present a docking model that ranks compounds according to their potential effectiveness as a potential substrate or inhibitor. We utilize xanthine oxidase (XO), a multi-cofactor oxido-reductase which converts hypoxanthine to xanthine and xanthine to uric acid. During the reductive half reaction, electrons flow from the molybdopterin, to each of two Fe/S centers, and finally to FAD. During the oxidative half reaction, electrons are passed from the FAD to O2. Under ideal physiological conditions, this reduction of oxygen generates H2O2 and, under multiple turnover conditions, superoxide in amounts which is regulated by catalase and superoxide dismutase. Utilizing computer modeling predictions of the docking orientations and energies of a group of purine based structures was selected. Correlating computer estimations with steady state kinetic data, a rapid screening process for inhibittor prediction was highlighted. This method allows educated selection of likely inhibitors, thereby decreasing the time and supplies required to complete a traditional kinetic analysis screening. Results demonstrate the functionality and reliability of this method and have proven particularly useful in understanding binding orienttations or poses of each compound.
Here we present a docking model that ranks compounds according to their potential effectiveness as a potential substrate or inhibitor. We utilize xanthine oxidase (XO), a multi-cofactor oxido-reductase which converts hypoxanthine to xanthine and xanthine to uric acid. During the reductive half reaction, electrons flow from the molybdopterin, to each of two Fe/S centers, and finally to FAD. During the oxidative half reaction, electrons are passed from the FAD to O2. Under ideal physiological conditions, this reduction of oxygen generates H2O2 and, under multiple turnover conditions, superoxide in amounts which is regulated by catalase and superoxide dismutase. Utilizing computer modeling predictions of the docking orientations and energies of a group of purine based structures was selected. Correlating computer estimations with steady state kinetic data, a rapid screening process for inhibittor prediction was highlighted. This method allows educated selection of likely inhibitors, thereby decreasing the time and supplies required to complete a traditional kinetic analysis screening. Results demonstrate the functionality and reliability of this method and have proven particularly useful in understanding binding orienttations or poses of each compound.
