EnzyKR: a chirality-aware deep learning model for predicting the outcomes of the hydrolase-catalyzed kinetic resolution
Xinchun Ran, Yaoyukun Jiang, Qianzhen Shao, Zhongyue Yang
Abstract
esterase. The performance of EnzyKR was compared against that of a recently developed kinetic predictor, DLKcat. EnzyKR correctly predicts the favored enantiomer and outperforms DLKcat in 18 out of 28 reactions, occupying 64% of the test cases. These results demonstrate EnzyKR to be a new approach for prediction of enantiomeric outcomes in hydrolase-catalyzed kinetic resolution reactions.
Topics & Concepts
Kinetic resolutionChirality (physics)CatalysisKinetic energyHydrolaseResolution (logic)Deep learningChemistryArtificial intelligenceComputer scienceCombinatorial chemistryEnzymePhysicsOrganic chemistryEnantioselective synthesisClassical mechanicsNuclear physicsNambu–Jona-Lasinio modelChiral symmetry breakingQuarkProtein Structure and DynamicsMicrobial Metabolic Engineering and BioproductionComputational Drug Discovery Methods