Enzyme Catalysis and Immobilization

Accelerated enzyme engineering by machine-learning guided cell-free expression

The paper develops a machine learning-guided cell-free platform to accelerate enzyme engineering by mapping sequence-function relationships and optimizing enzymes for multiple chemical reactions.

Active Learning-Assisted Directed Evolution

This paper introduces ALDE, a machine learning-assisted directed evolution method that improves protein engineering outcomes by efficiently exploring epistatic mutation spaces.

Plasma-driven biocatalysis using the cytochrome P450 enzyme CYP152BSβ

This study demonstrates plasma-driven biocatalysis using CYP152BSβ to convert non-natural substrates, achieving a turnover number of 18.82 mol(R)-1-PhOl.

Engineering surface electrostatics affords control over morphological preference, synergy, and activity in polymer degrading enzymes

This study redesigns the surface charge of a PET-hydrolase to enhance its activity and morphological preference, revealing synergistic interactions with the wildtype enzyme.

Mirages in continuous directed enzyme evolution: A cautionary case study with plantized bacterial THI4 enzymes

The paper shows that synonymous mutations, not nonsynonymous ones, drove growth improvements in bacterial THI4 enzymes adapted for plant use through continuous directed evolution.

Influence of ionic liquids on enzymatic asymmetric carboligations

This study shows that ionic liquids affect enzyme activity and enantioselectivity in carboligation reactions, with specific IL cations altering selectivity patterns.

Immobilized Nucleoside 2'-Deoxyribosyltransferases from Extremophiles for Nucleoside Biocatalysis

This paper demonstrates the immobilization of NDT enzymes from extremophiles to enhance their stability, recyclability, and catalytic efficiency for nucleoside synthesis.

LevSeq: Rapid Generation of Sequence-Function Data for Directed Evolution and Machine Learning

LevSeq rapidly generates sequence-function data for protein engineering using nanopore sequencing and dual barcoding, enabling directed evolution and machine learning applications.

A One-Pot Biocatalytic Cascade to Access Diverse L-Phenylalanine Derivatives from Aldehydes or Carboxylic Acids

This paper describes a one-pot biocatalytic cascade using PLP-dependent enzymes to synthesize diverse L-phenylalanine derivatives from aldehydes and carboxylic acids under mild conditions.

Direct observation of assembly and function of trigger responsive lipase biohybrids

This study synthesizes and characterizes pH and temperature responsive lipase-polymer biohybrids, showing increased enzymatic activity and stability compared to native lipases.

Enhancing the Reverse Transcriptase Function in Taq Polymerase via AI-driven Multiparametric Rational Design

This paper uses AI-driven rational design and wet-lab analysis to create Taq polymerase mutants with enhanced reverse transcriptase activity while maintaining other key properties.

Efficient synthesis of arabinosyl nucleosides via active site engineering of the Leishmania mexicana purine 2'-deoxyribosyltranferase

This paper reports engineered variants of Leishmania mexicana purine deoxyribosyltransferase with enhanced arabinosyltransferase activity for synthesizing vidarabine, without compromising thermal stability.

A language model assistant for biocatalysis

This paper introduces LM-ABC, a language model assistant for biocatalysis that streamlines enzyme engineering workflows using natural language inputs and integrates with computational tools.

Magnetic Protein Aggregates Generated by Supramolecular Assembly of Ferritin Cages - A Modular Strategy for the Immobilization of Enzymes

This paper introduces a method to produce magnetic protein aggregates (MPAs) in vivo for enzyme immobilization, demonstrating their magnetic properties and ability to functionally attach enzymes.

Navigating directed evolution efficiently: optimizing selection conditions and selection output analysis

This study optimizes directed evolution protocols by analyzing selection conditions and sequencing coverage to improve efficiency and accuracy in identifying enriched mutants.

Harnessing P450 enzyme plasticity for generalizable peptide biaryl macrocyclization

This paper identifies a versatile P450 enzyme, GpeC, capable of catalyzing peptide biaryl macrocyclization across diverse substrates and demonstrates its application in synthesizing natural products.

Machine learning guided rational design of a non-heme iron-based lysine dioxygenase improves its total turnover number

This paper uses machine learning and molecular dynamics to design improved variants of a non-heme iron-dependent lysine dioxygenase, achieving higher turnover numbers.

From Bulk to Binding: Decoding the Entry of PET into Hydrolase Binding Pockets

The paper uses molecular dynamics simulations to uncover the binding pathway of PET hydrolases into PET material and identifies key residues affecting PET entry.

Single Distal Mutation Enhances Activity of known PETases via Stabilisation of PET-binding

The paper reports an engineered PETase, Fast_2.9, with enhanced activity and stability for PET degradation, identified through high-throughput screening of PET nanoparticles.

Pore engineering as a general strategy to improve protein-based enzyme nanoreactor performance

This paper introduces a pore-engineered enzyme nanoreactor platform based on encapsulins to improve catalytic activity and substrate range.

Rational Design of a Flavoenzyme for Aerobic Nicotine Catabolism

The paper rationally designs a flavoenzyme Pnao with improved aerobic nicotine catabolism, showing activity in rat serum and identifying key residues for enzyme specificity.

Overcoming the challenges of cascade reactions and complex substrates in natural product biocatalysis: Immobilization of a cyclodipeptide synthase.

This paper immobilizes a cyclodipeptide synthase on three supports to enable stable, recyclable production of the cyclic dipeptide cHE, demonstrating the feasibility of using immobilized enzymes with complex substrates.

Discovery of Novel R-Selective Aminotransferase Motifs through Computational Screening

The paper identifies novel motifs in R-selective aminotransferase enzymes through computational screening and motif analysis.

Protein Language Models in Directed Evolution

This paper demonstrates how protein language models can guide directed evolution to improve PET degradation enzyme variants.

Controllable multi-halogenation of a non-native substrate by SyrB2 iron halogenase

This paper demonstrates how SyrB2 iron halogenase can controllably halogenate non-native substrates to produce mono-, di-, and tri-chlorinated products by adjusting cofactor loading and electron transfer.

Engineering Candida boidinii formate dehydrogenase for activity with NMN(H)

The paper attempts to engineer Candida boidinii formate dehydrogenase to use NMN+ as a cofactor but finds that designed mutations either fail to enhance activity or disrupt enzyme function entirely.

Modulation of Ideonella sakaiensis PETase active site flexibility and activity on morphologically distinct substrates by surface charge engineering

The paper investigates how surface charge mutations affect PETase activity on different PET substrates and identifies an engineered variant with improved degradation efficiency.

Synthesis of alkyl glucosides catalyzed by immobilized α-amylase from Thermotoga maritima

This study immobilizes α-amylase from Thermotoga maritima on different supports to enhance its stability in alcoholysis reactions, achieving high residual activity and octyl glucoside production.

Protein fusion strategies for a multi-component Rieske oxygenase

This study evaluates protein fusion strategies to simplify the multi-component electron transfer chain of a Rieske oxygenase, showing that fusing CDO-Red to CDO-Fd enables efficient oxygenase activation and product formation.

Enhanced Sequence-Activity Mapping and Evolution of Artificial Metalloenzymes by Active Learning

This paper improves enzyme engineering by combining active learning and experimental screening to efficiently discover high-performing artificial metalloenzymes.