Enzyme Catalysis and Immobilization

This paper demonstrates the directed evolution of a multimodal plastic-degrading enzyme capable of breaking down both polyesters and polyurethane.

This study engineers HPD variants with enhanced NTBC tolerance to restore tyrosine metabolism while maintaining catalytic activity and MHC-II binding properties.

This study compares dual-enzyme spore display with mixed single-enzyme spores for cellulose hydrolysis, finding that mixing single-enzyme spores yields higher glucose production.

AlphaVariant uses reinforcement learning with evolutionary priors to optimize enzyme variants from sparse experimental data, achieving high activity improvements in multiple rounds of optimization.

Unattended droplet-microfluidic Bayesian optimization of a glycerol detection cascade matched design of experiments (DoE) with one third of the conditions; a second cascade used DoE with Raman readout.

This paper designs enantioselective photoenzymes using deep learning methods to precisely position a photosensitizer and substrate, achieving high stereocontrol and regiocontrol.

This paper introduces a computational pipeline for de novo metalloenzyme design using Metal Mer, achieving high selectivity and activity in catalytic reactions without directed evolution.