Enzyme Catalysis and Immobilization

Directed Evolution of Multimodal Plastic Degrading Enzymes

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

Tuning inhibitor susceptibility of human 4-hydroxyphenylpyruvate dioxygenase to rescue tyrosine catabolism in the presence of β-triketones

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

Recombinant spore-displayed enzymes for cellulose hydrolysis: dual-enzyme spores versus mixed single-enzyme spores

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.

Reinforcement learning with evolutionary priors unlocks multi-site enzyme optimization from sparse experimental feedback

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

CascadeMAP: Autonomous Closed-loop Optimization of Enzyme Cascades via Microfluidics, Machine Learning and Agentic AI

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.

Design of enantioselective photoenzymes by scaffolding mirror image catalytic sites

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

Synthetic biology-guided modular engineering of the secreted cutinase FoCut5a with a carbohydrate-binding module improves poly(ester-urethane) depolymerization in Yarrowia lipolytica

De novo design of metalloenzymes using Metal Mer

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.

Photobiocatalytic Diastereo- and Enantioselective Synthesis of Non-Canonical Amino Acids Bearing Challenging Stereochemical Dyads and Triads

This paper develops engineered PLP-dependent biocatalysts for stereodivergent synthesis of non-canonical amino acids with complex stereochemical arrays, achieving high stereoselectivity and yield.

Iterative computational bioprospecting of hydroxymethylfurfural oxidases combining molecular simulation and machine learning

The paper identifies improved hydroxymethylfurfural oxidases through iterative computational methods combining molecular simulation and machine learning.

Design-Evolution Synergy Enables New-to-Nature Enzyme Chemistry

This study combines design and evolution to create new-to-nature enzymes capable of performing regio- and enantioselective C-H amination reactions for synthesizing chiral piperidines.

Asymmetric assembly of congested contiguous stereocenters via photobiocatalytic three-component radical coupling

This paper introduces a photobiocatalytic three-component radical coupling method that enables the stereoselective assembly of congested stereocenters using evolved biocatalysts and photosensitizers.

AI-Guided Multi-Objective Engineering of Glucoamylase Enables Acidification-Free Starch Saccharification

This paper uses AI to engineer a more stable and pH-tolerant glucoamylase variant, achieving higher starch conversion without acidification.

Megascale recombination generates millions of catalytically competent PETases

This study shows that large-scale recombination can generate millions of catalytically competent PETases compatible with high-throughput screening.

A binuclear copper enzyme platform for enantioconvergent radical (pseudo)halogenation

This study reprograms binuclear copper enzymes to catalyze enantioselective radical (pseudo)halogenation reactions, demonstrating superior activity and selectivity compared to nonheme Fe enzymes.

Substituting a conserved histidine alleviates difluoroacetate-dependent isoaspartate formation in a fluoroacetate dehalogenase

This study identifies a conserved histidine residue critical for fluoroacetate dehalogenase activity on difluoroacetate and shows substitutions enhance its catalytic efficiency.

Integrating complementary biological information for multi-objective enzyme engineering

This study develops a machine learning framework to engineer enzymes by integrating sparse data with evolutionary and structural information, achieving improvements in catalytic performance, yield, and stability.

High-throughput physics-based enzyme engineering

This paper introduces a physics-based framework for enzyme engineering that combines machine learning and molecular mechanics to predict catalytic rates and selectivity with high accuracy.

Multistate Enzyme Design Enables Efficient and Stereoselective Multistep Catalysis

This paper introduces multistate enzyme design to optimize active sites across reaction coordinates, achieving higher catalytic efficiency and enantioselectivity than single-state designs.

Reframing enzyme function prediction as conditional generation

Fluxion generates enzyme function predictions by modeling electron flow trajectories, enabling function generation beyond static classification.

Direct measurement of PET hydrolase interfacial kinetics reveals catalysis-independent surface remodelling

This paper directly measures PET hydrolase interfacial kinetics on solid polymer surfaces, revealing catalysis-independent surface remodelling during enzyme binding.

Ancestors of Arylmalonate Decarboxylase show increased Activity, Stability and Stereoselectivity

Ancestral sequence reconstruction of a bacterial decarboxylase gave enzymes with up to 294-fold longer half-life at 45 °C, higher activity, and 99.7% ee on a vinyl malonate substrate.

Learning protein function through autonomous experimental interaction

This paper demonstrates an AI system that autonomously interacts with biological systems to discover new protein functions through continuous experimental feedback.

Combining Machine Learning and Directed Evolution for Optimization of a Monooxygenase

This study combines machine learning and directed evolution to optimize the monooxygenase HpaBC for improved L-Dopa production activity.

Gram-scale one-pot enzymatic synthesis of CDP-ribitol by a designed bifunctional fusion enzyme

This paper describes a one-pot enzymatic method to produce CDP-ribitol at gram scale using a bifunctional fusion enzyme, achieving high yield and atom economy.

Conformation of the Catalytic Lysine is a Key Determinant of 2-Deoxyribose-5-phosphate Aldolase (DERA) Stereoselectivity

This study identifies the conformation of catalytic lysine as a key determinant of DERA stereoselectivity through structural and biochemical analyses.

Efficient and low-impact enzymatic glycosylation with robust sucrose synthase variants

The paper reports engineered sucrose synthase variants with enhanced activity and stability for efficient glycosylation, achieving high conversion yields and reduced environmental impact.

Machine Learning-Assisted Evolution of Broadly Functional Enzyme Libraries

This paper uses machine learning to guide the creation of enzyme libraries with broader catalytic activity, showing improved performance across multiple reactions.

Combining Stability-Centered Atomistic Design with Machine Learning for Targeted Enzyme Optimization

This paper introduces MLEE, a machine learning-assisted enzyme engineering workflow that improves hit rates for high-fitness enzyme variants compared to traditional methods.

Function-guided design of active enzymes

The paper presents a framework for designing active enzymes from functional descriptions, achieving high catalytic activity in synthesized designs.