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At least 19 recordsLinked to original sources
PubMed2026

Genomic prospecting and biochemical characterization of a novel thermostable 3-quinuclidinone reductase from hot spring metagenomes for efficient biocatalysis.

This study presents the discovery and characterization of a novel thermophilic 3-quinuclidinone reductase (ScQR) identified through metagenomic mining of hot spring environments. ScQR, a member of the short-chain dehydrogenase/reductase (SDR) superfamily, was heterologously expressed in Escherichia coli, and its catalytic properties were systematically characterized. The enzyme demonstrates exceptional thermal stability, retaining 86% of its activity after 48 hours at 70°C. Furthermore, K+ and Mg²+ ions significantly enhanced ScQR's activity at specific concentrations. Structural analysis revealed that ScQR adopts a typical SDR fold with a conserved catalytic triad (S141-Y155-K159), and it is NAD(H) dependent. Enzyme assays indicated that ScQR is highly stereoselective for (R)-3-quinuclidinol, with no activity against its enantiomer, (S)-3-quinuclidinol. The enzyme exhibits optimal activity at pH 9 and 85°C, making it a promising candidate for industrial applications requiring high thermal stability. Molecular dynamics simulations further revealed that ScQR preserves global structural integrity up to 360 K, whereas higher temperatures induce destabilization, predominantly in the C-terminal region and residues 95-100. In addition, structure-guided computational design enabled by LigandMPNN and UniKP yielded three ScQR variants with improved substrate affinity and catalytic efficiency while maintaining the overall fold and function. This work underscores the power of metagenomics with structure-driven protein design in discovering novel enzymes with unique catalytic properties from extreme environments and establishes ScQR as a promising biocatalyst for biotechnological and pharmaceutical applications.IMPORTANCEThis study reports the discovery of ScQR, a novel thermophilic 3-quinuclidinone reductase identified via metagenomic mining. ScQR represents one of the most heat-resistant members of the SDR superfamily discovered to date, maintaining 86% activity after 48 hours at 70°C. These findings establish ScQR as a robust biocatalyst for high-temperature pharmaceutical applications and demonstrate a scalable workflow for optimizing enzymes from extreme environments, offering significant value to the fields of biocatalysis and protein engineering.

computational design↗
PubMed2026

Generative artificial intelligence for enzyme design and biocatalysis.

Sparked by innovations in generative artificial intelligence (AI), the field of protein design has undergone a paradigm shift with an explosion of new models for optimizing existing enzymes or creating them from scratch. After more than one decade of low success rates for computationally designed enzymes, generative AI models are now frequently used for designing proficient enzymes. Here, we provide a comprehensive overview and classification of generative AI models for enzyme design, highlighting models with experimental validation relevant to real-world settings and outlining their respective limitations. We argue that generative AI models now have the maturity to create and optimize enzymes for industrial applications. Wider adoption of generative AI models with experimental feedback loops can speed up the development of biocatalysts and serve as a community assessment to inform the next generation of models.

Biocatalysis↗
PubMed1976

Pancreatic lipase and colipase: an example of heterogeneous biocatalysis.

The hydrolytic reactions catalyzed by pancreatic lipase represent a good example of heterogeneous catalysis. The particularity of this enzyme is provided by its preferential action on emulsified substrates. The first step of catalysis resides in a reversible adsorption of the enzyme to the oil-water interface. In fact, the formation of this adsorption complex is an obligatory step for the enzyme to display its full activity. Two principal but not necessarily exclusive hypotheses have been proposed to explain the observed interfacial activation: Either the interface confers new properties on the substrate which allow its subsequent hydrolysis, or the enzyme itself is modified by adsorption at the interface. Different approaches have recently been developed to clarify this point further. The results obtained by chemical modifications of lipase are consistent with the following hypothesis. The active site preexists in solution and becomes fully functional only by interaction of the interface with an additional site on the enzyme molecule which can be tentatively called the "interfacial activation site." Finally, a protein of low molecular weight, colipase, seems necessary for lipase to express its activity under physiological conditions. This protein enters specific interactions with bile salts micelles and is responsible for the reversal of the inhibition of lipolysis brought about by these detergents.

Animals↗
PubMed2025

Decoding the distribution, structure-function-redox potential relationship and recent advances in fungal laccases: a systematic approach.

Laccases, categorized as multicopper oxidases, are recognized for their multifaceted roles in ecosystems and their utility in diverse industrial applications. Laccases from higher fungi, specifically Ascomycota and Basidiomycota, have garnered significant research interest due to their elevated redox potentials and their capacity to degrade lignin in decaying wood, alongside other industrial uses. Here, we have conducted a comprehensive and systematic analysis on fungal laccases using Web of Science, Scopus, PubMed, and ScienceDirect. The genomic distribution, phylogenetic affiliation, and structural organization of laccase-encoding genes in higher fungal species were investigated, as were the catalytic mechanisms of the corresponding enzymes. Additionally, the study explores the correlation between structural domains and redox potential, as well as the impact of post-translational modifications like glycosylation on enzyme activity. Furthermore, the recent advancements in laccase engineering, employing strategies such as rational design, directed evolution, and heterologous expression are discussed. The review also explores the scope of "artificial intelligence and machine learning" in deducing the structure-function relationships, optimizing codon usage, predicting signal peptides, enhancing enzymatic performance, and developing host-specific genetic engineering techniques is also discussed for tailoring fungal laccases to meet the demands of industrial biocatalysis for improved activity and stability.

Laccase↗
PubMed2026

Prediction of bacterial protein-compound interactions with only positive samples.

MOTIVATION: Prediction of Compound-Protein Interactions (CPI) in bacteria is crucial to advance various pharmaceutical and chemical engineering fields, including biocatalysis, drug discovery, and industrial processing. However, current CPI models cannot be applied for bacterial CPI prediction due to the lack of curated negative interaction samples. RESULTS: We propose a novel Positive-Unlabeled (PU) learning framework, named BIN-PU, to address this limitation. BIN-PU generates pseudo positive and negative labels from known positive interaction data, enabling effective training of deep learning models for CPI prediction. We also propose a weighted positive loss function that weights to truly positive samples. We have validated BIN-PU coupled with multiple CPI backbone models, comparing the performance with the existing PU models using bacterial cytochrome P450 (CYP) data. Extensive experiments demonstrate the superiority of BIN-PU over the benchmark models in predicting CPIs with only truly positive samples. Furthermore, we have validated BIN-PU on additional bacterial proteins obtained from literature review, human CYP datasets, and uncurated data for its reproducibility. We have also validated the CPI prediction for the uncurated CYP data with biological and biophysical experiments. BIN-PU represents a significant advancement in CPI prediction for bacterial proteins, opening new possibilities for improving predictive models in related biological interaction tasks. AVAILABILITY AND IMPLEMENTATION: The source code and data are available at https://github.com/datax-lab/CYP.

Bacterial Proteins↗
PubMed2025

Genetic Incorporation of a Thioxanthone-Containing Amino Acid for the Design of Artificial Photoenzymes.

Genetically encodable photosensitizers allow the design of artificial photoenzymes to expand the scope of abiological reactions. Herein, we report the genetic incorporation of a thioxanthone-containing amino acid into a protein scaffold via an engineered pyrrolysyl-tRNA/pyrrolysyl-tRNA synthetase pair. The designer enzyme was engineered to catalyze a dearomative [2+2] cycloaddition reaction in high yields (up to>99 % yield) with excellent enantioselectivity (up to 98 : 2 e.r.). This work provides a robust and facile method for photoenzyme design and lays the foundation for the development of further photoenzymatic reactions.

Xanthones↗
PubMed2026

A Pseudokinase Catalyzes Nitrile Formation in the Biosynthesis of a Potent Marine Toxin.

Several pseudokinases, previously regarded as dead enzymes due to the lack of catalytic residues, catalyze nucleotidylation. While they often utilize macromolecular substrates such as proteins and RNAs in primary metabolism, those acting on non-macromolecules in specialized metabolisms are limited. Calyculin A, a cytotoxic natural product produced by an uncultured sponge symbiont, possesses a unique nitrile group at the end of its tetraene tail. Even though its biosynthetic gene cluster (BGC) has been identified, the enzyme responsible for nitrile formation remains unknown. Herein, through a comparative analysis of the BGCs for calyculin derivatives in symbiotic bacteria from distinct sources, we identified a novel nitrile-forming enzyme, CalN. While CalN lacks sequence homology with other known nitrile-forming enzymes, it is structurally similar to pseudokinases. In vitro enzymatic reactions demonstrated that CalN specifically catalyzes nitrile formation through the adenylation of an amide substrate, calyculinamide A. In silico analyses and mutational experiments showed that CalN's structure features a unique insertion that plays critical roles in ATP recognition and the spatial coordination of catalytic residues. This study not only identifies a new family of nitrile-forming enzymes but also expands the variety of chemical reactions mediated by pseudokinases in nature.

Marine Toxins↗
PubMed2026

Marine Vibrio Biocatalysts as Unique Green Transformation (GX) Tools at the Time to Sustainable Development Goals (SDGs).

Vibrios have sustained various types of ocean ecosystems, being key players in marine mineral cycles and essential partners in specific groups of marine life. Observed genome plasticity and metabolic versatility are some of the unique biological features of vibrios, and these traits could contribute in expanding their ecological niche in marine environments. Vibrios are now recognized as ecophysiologically essential microbial species for our planet. At the time to "Sustainable Development Goals" (SDGs), their genome plasticity and metabolic versatility have also been studied with the aim of solving global issues such as energy production and plastic pollution by creating new microbial biocatalysts. Here, we introduce recent progress on the application of vibrios aiming towards green transformation (GX).

Vibrio↗
PubMed2026

Unlocking the molecular engineering of Geobacillus glycoside hydrolases as a source of industrial biocatalysts.

This review examines Geobacillus sensu stricto as a source of thermostable glycoside hydrolases (GH) for biomass conversion, food processing, and enzyme engineering. Recent peer-reviewed literature was assessed with emphasis on taxonomy, genome-based Carbohydrate-Active Enzymes (CAZyme) prediction, biochemical validation, structural data, and engineering case studies. Taxonomic boundaries were interpreted using current Anoxybacillaceae frameworks, with Parageobacillus treated as a related comparator rather than as Geobacillus. The strongest evidence supports GH13 alpha-amylases, xylan-active systems, beta-xylosidases, and selected accessory enzymes. Recent studies also show that genome mining must be coupled with enzymatic assays and product profiling because CAZyme annotation alone does not prove industrial function. Molecular engineering has improved relevant traits, including the longer thermal half-life of engineered G. stearothermophilus alpha-amylase variants, the increased catalytic efficiency of oligo-alpha-1,6-glucosidase variants, and improved AmyS expression in Bacillus subtilis. Geobacillus glycoside hydrolases are best interpreted as process-specific, engineerable biocatalytic templates. Their translation requires reliable taxonomy, functional validation, structural interpretation, scalable expression and testing on realistic substrates. This synthesis also recognises current limitations: many predicted CAZymes still lack biochemical validation, complete cellulolytic systems remain less mature than xylan- and starch-active systems, and scale-up data remain scarce.

Geobacillus↗
PubMed2025

Functional metaproteomics for enzyme discovery.

Discovery of microbial biocatalysts traditionally relied on activity screening of isolated bacterial strains. However, since most microorganisms cannot be cultivated in the lab, such an approach leaves the majority of the microbial enzyme diversity untapped. Metagenomic approaches, in which the DNA from a microbial community is directly isolated and then used either for the creation of an expression library or for sequencing and metagenome annotation have alleviated this shortcoming to an extent, but have their own limitations: the generation of large expression libraries is time-consuming and their screening is costly, while metagenome annotation can infer biocatalytic function only from prior knowledge. We have thus developed a functional metaproteomic approach, which combines the immediacy of traditional activity screening with the comprehensiveness of a meta-omics approach. Briefly, the whole metaproteome of an environmental sample is separated on a 2-D gel, biocatalytically active proteins are visualized in-gel through zymography, and those candidate biocatalysts are then identified through mass spectrometry, searching against a metagenome-derived database obtained from the very same environmental sample. Here we explain the process in detail, with a focus on esterases, and give guidelines on how to develop a functional metaproteomic workflow for enzyme discovery.

Proteomics↗
PubMed2026

Discovery and engineering of enzymes for new-to-nature photobiocatalysis.

Photobiocatalysis integrates enzymatic catalysis with photochemistry, enabling challenging radical transformations with high selectivity under mild conditions. Early developments in this field were largely driven by the discovery that enzyme-bound cofactors can form photoactive charge-transfer complexes with substrates, thereby initiating radical chemistry upon light irradiation. Recent advances, however, have substantially expanded the mechanistic landscape of photobiocatalysis through diverse mechanisms. This review summarizes major developments in photobiocatalysis reported since 2024. Rather than cataloging individual reactions, we focus on the fundamental mechanisms of radical generation and interception within enzyme active sites, and discuss how these mechanistic principles guide the discovery, engineering, and design of enzymes for new-to-nature photobiocatalysis.

Protein Engineering↗
PubMed2026

Bioprospecting microbial genomes to expand the biocatalytic toolbox of rubber oxygenases.

A set of rubber oxygenases was discovered through phylogenetic analysis and AI-based structural modeling of complexes of the putative enzymes with a substrate mimicking cis-1,4-polyisoprene. Sixteen candidate proteins were selected from thermophilic microorganisms, all sequence-related to the Latex clearing protein from Streptomyces sp. K30 (LcpK30). Sequence truncation and solubility tags were then evaluated to enhance protein expression, with the SUMO tag proving to be the most effective. Including LcpK30, nine heme-containing oxygenases were successfully expressed in E. coli NEB 10-beta cells, purified (35-157 mg L-1 yield) and characterized. Steady-state kinetics revealed significant rubber latex-degrading properties for six of them, with the truncated SUMO-fused LcpK30 (SUMO-LcpK30T) showing activity in agreement with literature. Notably, the catalytic efficiencies of all the expressed homologs lay within one order of magnitude and the oxygenase from Thermomonospora echinospora was found to be particularly promising in terms of activity, especially at high latex concentrations (more than 1% w/v). The analysis of reaction mixtures by both HPLC and HPLC-MS confirmed the oxidation of cis-1,4-polyisoprene to form the expected isoprenoid oligomers (n = 2-12), whose distribution was consistent with the usual endo-type cleavage pattern in all but one case. This bioprospecting effort afforded a platform of new rubber-degrading enzymes with diverse efficiencies and product profiles, capable of adapting to targeted applications.

Oxygenases↗
PubMed2026

Structural Characterization and Engineering of a GH134 β-Mannanase from Aspergillus nidulans for Enhancement of Activity and Stability.

Mannans are abundant plant hemicelluloses, and endo-β-mannanases are important biocatalysts for their conversion into functional manno-oligosaccharides. Here, we report the structural and functional characterization of a glycoside hydrolase family 134 β-mannanase from Aspergillus nidulans (AnGH134) and a structure-guided engineering strategy to improve its performance on locust bean gum. The 1.75 Å crystal structure reveals the conserved lysozyme-like fold of GH134 enzymes and supports an inverting catalytic mechanism with Glu43 and Asp55 as the putative catalytic residues. Docking, mutational, and molecular dynamics analyses indicate that AnGH134 uses an extended substrate-binding groove and that groove-exit residues and the C-terminal region contribute to productive catalysis. Guided by these findings, N-terminal fusion of CBM10 enhanced catalytic efficiency and thermal stability, whereas C-terminal fusion was detrimental. These results provide a framework for engineering GH134 mannanases.

Aspergillus nidulans↗
PubMed2025

Aminoacyl-tRNA Specificity of a Ligase Catalyzing Non-ribosomal Peptide Extension.

Peptide aminoacyl-transfer ribonucleic acid ligases (PEARLs) are amide-bond-forming enzymes that extend the main chain of peptides by using aminoacyl-tRNA (aa-tRNA) as a substrate. In this study, we investigated the substrate specificity of the PEARL BhaBCAla from Bacillus halodurans, which utilizes Ala-tRNAAla. By leveraging flexizyme, a ribozyme capable of charging diverse acids onto a desired tRNA, we generated an array of aa-tRNAs in which we varied both the amino acid and the tRNA to dissect the substrate scope of BhaBCAla. We demonstrate that BhaBCAla catalyzes peptide extension with noncognate proteinogenic and noncanonical amino acids, hydroxy acids, and mercaptocarboxylic acids when attached to tRNAAla. For most of these, the efficiency was considerably reduced compared to Ala, indicating that the enzyme recognizes the amino acid. By variation of the different parts of the tRNA, enzyme specificity was shown to also depend on the acceptor stem and the anticodon arm of the tRNA. These findings establish the molecular determinants of PEARL specificity and provide a foundation for engineering these enzymes for broader applications in peptide synthesis.

RNA, Transfer, Amino Acyl↗
PubMed2025

Insights into the Catalytic Activity of a Metagenome-Derived Urethanase.

The discovery of urethanases shows an opportunity to access the biotechnological recycling of polyurethane-based plastics (PURs), widely used in the manufacture of everyday materials. However, the mechanistic understanding of these enzymes remains under debate. In this work, we report a QM/MM-based mechanistic study of the metagenome-derived urethanase UMG-SP2 catalyzing the degradation of a urethane-like model compound, 4-nitrophenyl benzylcarbamate (pNC). A high-quality structural model generated with AlphaFold2, prior to the availability of the crystal structure, accurately captured the Ser-Ser-Lys catalytic triad characteristic of amidase signature enzymes. Highly accurate constant-pH nonequilibrium molecular dynamics and Monte Carlo (neMD/MC) simulations provided the full titration curve of active site Lys, explaining the need for alkaline media for the enzyme to be active. The generation of the free energy landscape, obtained by means of free energy perturbation methods with the M06-2X DFT functional describing the QM region of the full system, reveals an esterase-like three-step mechanism of UMG-SP2, i.e., acylation, hydrolysis, and decarboxylation, with all steps being kinetically feasible. Our computational results show very good agreement with experimental kinetic data, with a calculated free energy barrier of 21.2 kcal·mol-1 for the rate-determining step compared to 22.9 kcal·mol-1 derived from the experimentally measured turnover frequency (TOF). The present results also open the door for the final decarboxylation occurring in the solution after the release of the product of the hydrolysis step or within the active site. These findings provide an atomistic insight into the urethanase function and establish a robust framework for the future design of biocatalysts targeting polyurethane degradation.

Metagenome↗
PubMed2026

Unconventional Biocatalytic Strategies Orchestrate the Synthesis of the Nucleoside Analog Sinefungin.

Sinefungin is a potent nucleoside antimetabolite of S-adenosylmethionine (SAM). Since its discovery in the 1970s, sinefungin has generated significant scientific interest owing to its role as a bioisostere of SAM and its broad range of biological activities. Despite considerable efforts to uncover the enzymes responsible for sinefungin production in the following years, its biosynthesis remained unclear for decades. Here, we characterize the complete sinefungin biosynthetic gene cluster (sin BGC) from Streptomyces incarnatus NRRL 8089. In vitro and in vivo analyses support a recent finding that the defining carbon-carbon (C-C) bond is formed not by a long-hypothesized PLP-dependent process, but by a vitamin B12-dependent radical SAM enzyme. We provide direct mechanistic evidence, via isotope-labeled products, that the adenosyl group of sinefungin originates from adenosylcobalamin and is atypically consumed via a homolytic SH2 substitution reaction. We also characterize two peptide aminoacyl-tRNA ligases (PEARLs) that append alanines onto the nucleoside scaffold using tRNA-activated amino acids. The PEARLs act directly on small molecules rather than macromolecular substrates, with one PEARL capable of iterative elongation. In addition, we perform in-vitro substrate profiling of several sin BGC-encoded enzymes. We reveal that multiple enzymes show specificity toward phosphorylated intermediates, including the earliest-acting PEARL enzyme. These observations provide an explanation for a cryptic phosphorylation-dephosphorylation strategy observed in the pathway, as they prevent the formation of the highly toxic sinefungin inside the cell. Finally, we leverage these enzymes in a reduced multi-enzyme cascade to biosynthesize sinefungin. Together, these findings expand upon our current knowledge of radical-mediated C-C bond formation and PEARL enzyme catalysis, unlocking biocatalytic possibilities to produce amino acid-nucleoside conjugates.

Streptomyces↗