Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include training a neural network and predicting structural feature sets with the neural network. The operations may include producing predicted structures with the neural network using the structural feature sets, converting the predicted structures into predicted graphs with predicted edges, and comparing predicted graphs to training graphs and predicted edges to training edges to obtain a comparison. The operations may include training a model with the comparison, constructing a graph with the neural network using a node feature set, and reducing missing edges in the graph with the model.

Abstract: The present invention refers to Amadoriase enzyme protein variants having de-glycating activity and improved thermostability compared to the wild type Amadoriase. The present invention refers also to the use of the thermostabilized Amadoriase as deglycating agent, preferably in the food industry. Moreover, the present invention refers to the use of the thermostabilized Amadoriase as diagnostic and/or therapeutic tools. Preferably, the Amadoriase enzyme protein variants of the invention can be used for determining the level of glycated haemoglobin in a biological sample and therefore for monitoring diabetes.

Abstract: The present invention refers to Amadoriase enzyme protein variants having de-glycating activity and improved thermostability compared to the wild type Amadoriase. The present invention refers also to the use of the thermostabilized Amadoriase as deglycating agent, preferably in the food industry. Moreover, the present invention refers to the use of the thermostabilized Amadoriase as diagnostic and/or therapeutic tools. Preferably, the Amadoriase enzyme protein variants of the invention can be used for determining the level of glycated haemoglobin in a biological sample and therefore for monitoring diabetes.