Ai Predicts The Work Rate Of Enzymes

A team of bioinformaticians from Heinrich Heine University Düsseldorf (HHU) has developed a tool for predicting the turnover number (kcat) of various enzymes using AI methods. The tool, called TurNuP, uses deep learning models to convert information about the enzymes and catalysed reactions into numerical vectors, which are then used as the input for a machine learning model to predict the kcat turnover numbers. The tool was published in the scientific journal Nature Communications.