AI enantioselectivity predictor set to power computational catalyst screening

An image showing the reaction-based machine learning representations for predicting the enantioselectivity of organocatalysts

Source: © Raimon Fabregat/LCMD, EPFL

Workflow involves mapping a reaction representation onto the activation energy of the stereocontrolling step

Scientists in Switzerland have developed a machine learning method that can determine the enantioselectivities of reactions catalysed by complex organocatalysts. Key to the strong performance of this machine learning technique is a clever trick to avoid time-consuming calculations, enabled by an informed choice of molecular descriptors, reaction representations and feature engineering.