Enzyme Catalysis and Immobilization

Protein Scaffolds Modulate the Electronic Structure of a Common Ketyl Radical Intermediate in Thiamine Pyrophos-phate-Dependent Radical Biocatalysis: Insights from EPR and ENDOR Spectroscopy

This study uses EPR and ENDOR spectroscopy along with DFT to show how protein scaffolds alter the electronic structure of a ketyl radical intermediate in TPP-dependent radical biocatalysis, affecting enzyme reactivity.

Benchmarking and Experimental Validation of Machine Learning Strategies for Enzyme Engineering

This study benchmarks machine learning models for enzyme engineering using a curated dataset, finding zero-shot predictors are most generalizable but still modestly correlated with activity, with consensus models improving precision.

Multicatalytic cooperativity enables divergent photobiocatalytic C-C couplings for scaffold diversification

This study identifies new photobiocatalytic C-C couplings by combining PLP enzymes with photocatalysts, enabling the synthesis of non-canonical amino acids through directed evolution.

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.

Cellulase catalysis on cell surfaces using Caulobacter S-layer display

This study uses Caulobacter S-layer display to express functional cellulases for lignocellulosic biomass conversion, demonstrating synergistic catalytic activities.

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.

Loop engineering and activity improvement of TEV protease by a phagemid-based selection system

This study improves TEV protease activity through loop engineering using a phagemid-based selection system combined with deep learning.

Uncovering Functional Distant Mutations by Ultra-High-Throughput Screening of Dehalogenases

This study uses ultrahigh-throughput screening to identify mutations in dehalogenases that modulate substrate access and binding, revealing distal functional effects on enzyme dynamics.

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.

Coated Bacterial Enzymes: A one-step approach for enzymatic purification and immobilization

This paper introduces a one-step method for enzyme purification and immobilization using coated bacterial enzymes, demonstrating improved activity and stability compared to free enzymes.

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.

Multi-Objective Engineering of Fibrin-Selective Thrombolytic Proteases with Enhanced Biocatalytic Efficiency and Inhibition Resistance

This paper designs next-generation thrombolytic proteases with improved catalytic efficiency, fibrin selectivity, and inhibition resistance through multi-objective enzyme engineering.

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.

MPNN-guided redesign of PET hydrolases with enhanced catalytic activity below the PET glass transition temperature

This paper redesigns PET hydrolase PHL7 using MPNN models to enhance its catalytic activity at lower temperatures, achieving efficiency comparable to its activity at higher temperatures.

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.

Reprogramming the Rossmann Fold Signature Motif Creates Orthogonal Redox Biocatalysts

The paper reprograms the Rossmann fold motif to create NMN+-specific enzymes that avoid NAD(P)/H interactions, achieving high specificity and productivity in biotransformation.

Reframing enzyme function prediction as conditional generation

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