Abstract

With the increasing prevalence of gout and its etiological hyperuricemia, dietary control of gout based on low-purine food according to patients' eating habits is becoming a better choice compared to the existing drug treatment such as allopurinol with notorious side effects. Reconstructing the purine metabolic pathway in vitro to degrade purine substances in food into natural functional allantoin appears to be an innovative method for preparing nutritious and healthy food of low purine content. The present study reports a computer-assisted in vitro reconstruction of four purinolytic enzymes metabolizing adenosine into allantoin to reduce purine content in food for personalized dietary control of hyperuricemia and gout. Under the optimum reaction conditions of 40 °C and pH7, 0.1U of enzymes and 0.5 mmol L-1 adenosine determined by an orthogonal test design, 16 different enzyme complexes were experimentally tested. The tested enzyme composition and allantoin production values were used as input and output to build a three-layer back propagation artificial neural network (BP-ANN) model, which was further optimized by a genetic algorithm (GA). The optimum enzyme complex predicted by the GA-BP-ANN model produced 248.08±7.832 μmol L-1 allantoin, which was 19.9% higher than equimolar mixture of enzymes, and also more efficiently lowered purine contents in beer, as well as beef and yeast extracts. This is the first in vitro reconstitution of complete purine metabolic pathway by combining ANN and GA technologies, with successful application with respect to lowering the purine content in food, indicating a promising application of computer-assisted in vitro reconstitution of purinolytic pathway in low-purine food to prevent hyperuricemia and gout. © 2022 Society of Chemical Industry.

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