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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Thermostable Enzyme Variants in the Lower Mevalonate Pathway Improve Isoprenoid Production by Cell-Free Biocatalysis

Cell-free biocatalysis is a rapidly evolving field with great potential for sustainably producing valuable chemicals. Some challenges in cell-free biocatalysis include reaction longevity, enzyme stability, and the cost of the biocatalysts. Here, the challenge of enzyme instability was addressed by employing thermophilic enzymes to improve the productivity of the lower mevalonate pathway, using limonene as an example isoprenoid product. The Classical mesophilic mevalonate pathway was compared to a newly assembled set of thermophilic enzymes comprising the Archaea I mevalonate pathway. The thermophilic pathway enzymes were thermostable to at least 60 °C and exhibited a 6× longer operating lifetime at 22 °C. Thus, despite lower initial activity rates at ambient temperature, the thermophilic pathway was longer-lived and resulted in a more productive cell-free reaction overall, achieving 1.7× higher yield of limonene compared to using enzymes from mesophiles. Moreover, the thermostable pathway retained activity for longer with the challenge of solvent exposure, namely, ethanol and isoprenol, which broadens the scope of accessible substrates and/or products in cell-free reactions employing this pathway. Altogether, we showed significant improvement in the stability and productivity of the lower mevalonate pathway, which will enable more efficient cell-free biosynthesis of isoprenoid products. This represents a valuable strategy to increase the robustness of cell-free systems by carefully sourcing biocatalysts from thermophilic organisms, which have proven to be resilient to challenges unique to cell-free reaction systems.

09 BIOMASS FUELS↗
DOE OSTI2026

Encapsulation in a Bacterial Microcompartment Shell Improves Thermal Stability of a Glycolytic Enzyme

Selective encapsulation of target enzymes is an increasingly well-studied field, with a host of potential applications for biotechnology. Natively, many bacteria utilize bacterial microcompartments (BMCs) for enzyme encapsulation to enhance catalysis. BMCs are protein shells that enable selective localization of targeted metabolic enzymes and may improve catalytic rates by colocalizing pathway enzymes and/or serve to sequester toxic or volatile intermediates. The microcompartment shell of Haliangium ochraceum (HO) is a notable BMC chassis because of its modularity and versatility; it is easily expressed and assembled outside its native host and can accept a wide array of cargo. Recently, it was demonstrated that assembly of HO BMC shells can be easily achieved in vitro. Following up on our previous work on in vivo assembly of HO-BMCs with triose phosphate isomerase (TPI) as a model enzyme cargo, here we have demonstrated the advantages of in vitro assembly (IVA) for targeted enzyme encapsulation. We achieved variable loading of BMC shells with targeted amounts of TPI and demonstrated enhanced thermal stability of encapsulated TPI versus free TPI up to 62 °C.

assays↗
DOE OSTI2025

Enzyme property prediction using artificial intelligence

Artificial intelligence (AI)-driven enzyme property prediction enables rapid discovery and engineering of enzymes for a wide range of biotechnological and therapeutic applications. Here, we first introduce the key components in AI model development, including enzyme datasets, protein representation methods, and model architectures. We then highlight a variety of AI tools developed for the prediction of enzyme properties and functional annotations, including enzyme structure, kinetic parameters, substrate specificity, thermostability, solubility, Enzyme Commission number, and Gene Ontology term. Moreover, we describe representative downstream applications enabled by these AI tools. Finally, we discuss some challenges and opportunities as well as future prospects.

Yuan, Le [University of Illinois at Urbana-Champai↗
DOE OSTI2025

A [FeFe] Hydrogenase–Rubrerythrin Chimeric Enzyme Functions to Couple H 2 Oxidation to Reduction of H 2 O 2 in the Foodborne Pathogen Clostridium perfringens

[FeFe] hydrogenases are a diverse class of H 2 -activating enzymes with a wide range of utilities in nature. As H 2 is a promising renewable energy carrier, exploration of the increasingly realized functional diversity of [FeFe] hydrogenases is instrumental for understanding how these remarkable enzymes can benefit society and inspire new technologies. In this work, we uncover the properties of a highly unusual natural chimera composed of a [FeFe] hydrogenase and rubrerythrin as a single polypeptide. The unique combination of [FeFe] hydrogenase with rubrerythrin, an enzyme that functions in H 2 O 2 detoxification, raises the question of whether catalytic reactions, such as H 2 oxidation and H 2 O 2 reduction, are functionally linked. Herein, we express and purify a representative chimera from Clostridium perfringens (termed Cper HydR) and apply various electrochemical and spectroscopic approaches to determine its activity and confirm the presence of each of the proposed metallocofactors. The cumulative data demonstrate that the enzyme contains a surprising array of metallocofactors: the catalytic site of [FeFe] hydrogenase termed the H-cluster, two [4Fe-4S] clusters, two rubredoxin Fe(Cys) 4 centers, and a hemerythrin-like diiron site. The absence of an H 2 -evolution current in protein film voltammetry highlights an exceptional bias of this enzyme toward H 2 oxidation to the greatest extent that has been observed for a [FeFe] hydrogenase. Here, we demonstrate that Cper HydR uses H 2 , catalytically split by the hydrogenase domain, to reduce H 2 O 2 by the diiron site. Structural modeling suggests a homodimeric nature of the protein. Overall, this study demonstrates that Cper HydR is an H 2 -dependent H 2 O 2 reductase. Equipped with this information, we discuss the possible role of this enzyme as a part of the oxygen-stress response system, proposing that Cper HydR constitutes a new pathway for H 2 O 2 mitigation.

08 HYDROGEN↗
DOE OSTI2025

Efficient secretion of a plastic degrading enzyme from the green algae Chlamydomonas reinhardtii

Abstract Plastic pollution has become a global crisis, with microplastics contaminating every environment on the planet, including our food, water, and even our bodies. In response, there is a growing interest in developing plastics that biodegrade naturally, thus avoiding the creation of persistent microplastics. As a mechanism to increase the rate of polyester plastic degradation, we examined the potential of using the green microalgaChlamydomonas reinhardtiifor the expression and secretion of PHL7, an enzyme that breaks down post-consumer polyethylene terephthalate (PET) plastics. We engineeredC. reinhardtiito secrete active PHL7 enzyme and selected strains showing robust expression, by using agar plates containing a polyester polyurethane (PU) dispersion as an efficient screening tool. This method demonstrated the enzyme’s efficacy in degrading ester bond-containing plastics, such as PET and bio-based polyurethanes, and highlights the potential for microalgae to be implemented in environmental biotechnology. The effectiveness of algal-expressed PHL7 in degrading plastics was shown by incubating PET with the supernatant from engineered strains, resulting in substantial plastic degradation, confirmed by mass spectrometry analysis of terephthalic acid formation from PET. Our findings demonstrate the feasibility of polyester plastic recycling using microalgae to produce plastic-degrading enzymes. This eco-friendly approach can support global efforts toward eliminating plastic in our environment, and aligns with the pursuit of low-carbon materials, as these engineered algae can also produce plastic monomer precursors. Finally, this data demonstratesC. reinhardtiicapabilities for recombinant enzyme production and secretion, offering a “green” alternative to traditional industrial enzyme production methods.

Science & Technology - Other Topics↗
DOE OSTI2026

EC-Bench: A Benchmark for Enzyme Commission Number Prediction

Enzymes are proteins that catalyze specific biochemical reactions in cells. Enzyme Commission (EC) numbers are used to annotate enzymes in a four-level hierarchy that classifies enzymes based on the specific chemical reactions they catalyze. Accurate EC number prediction is essential for understanding enzyme functions. Despite the availability of numerous methods for predicting EC numbers from protein sequences, there is no unified framework for evaluating and studying such methods systematically. This gap limits the ability of the community to identify the most effective approaches for enzyme annotation. We introduce EC-Bench, a benchmark for EC number prediction, consisting of 1) an initial representative set of existing methods (including homology-based, deep learning, contrastive learning, and language model methods), 2) existing and novel accuracy and efficiency performance metrics, and 3) selected datasets to allow for comprehensive comparative study. EC-Bench is open-source and provides a framework for researchers to not only compare among existing methods objectively under uniform conditions, but also to introduce and effectively evaluate performance of new methods in a comparative framework. To demonstrate the utility of EC-Bench, we perform extensive experimentation to compare the existing EC number prediction methods and establish their advantages and disadvantages in a variety of prediction tasks, namely “exact EC number prediction”, “EC number completion” and (partial or additional) “EC number recommendation”. We find wide variation in the performance of different methods, but also subtle but potentially useful differences in the performance of different methods across tasks and for different parts of the EC hierarchy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Efficient secretion of a plastic degrading enzyme from the green algae Chlamydomonas reinhardtii

AbstractPlastic pollution has become a global crisis, with microplastics contaminating every environment on the planet, including our food, water, and even our bodies. In response, there is a growing interest in developing plastics that biodegrade naturally, thus avoiding the creation of persistent microplastics. As a mechanism to increase the rate of polyester plastic degradation, we examined the potential of using the green microalgaChlamydomonas reinhardtiifor the expression and secretion of PHL7, an enzyme that breaks down post-consumer polyethylene terephthalate (PET) plastics. We engineeredC. reinhardtiito secrete active PHL7 enzyme and selected strains showing robust expression, by using agar plates containing a polyester polyurethane (PU) dispersion as an efficient screening tool. This method demonstrated the enzyme’s efficacy in degrading ester bond-containing plastics, such as PET and bio-based polyurethanes, and highlights the potential for microalgae to be implemented in environmental biotechnology. The effectiveness of algal-expressed PHL7 in degrading plastics was shown by incubating PET with the supernatant from engineered strains, resulting in substantial plastic degradation, confirmed by mass spectrometry analysis of terephthalic acid (TPA) formation from PET. Our findings demonstrate the feasibility of polyester plastic recycling using microalgae to produce plastic-degrading enzymes. This eco-friendly approach can support global efforts toward eliminating plastic in our environment, and aligns with the pursuit of low-carbon materials, as these engineered algae can also produce plastic monomer precursors. Finally, this data demonstratesC. reinhardtiicapabilities for recombinant enzyme production and secretion, offering a “green” alternative to traditional industrial enzyme production methods.Graphical Abstract

Molino, João Vitor Dutra (ORCID:0000000324759807)↗
DOE OSTI2025

Thermodynamics shapes the in vivo enzyme burden of glycolytic pathways

Thermodynamically constrained reactions and pathways are hypothesized to impose greater protein demands on cells, requiring higher enzyme amounts to sustain a given flux compared to those with stronger thermodynamics. To test this, we quantified the absolute concentrations of glycolytic enzymes in three bacterial species— Zymomonas mobilis, Escherichia coli , and Clostridium thermocellum —which employ distinct glycolytic pathways with varying thermodynamic driving forces. By integrating enzyme concentration data with corresponding in vivo metabolic fluxes and ΔG measurements, we found that the highly favorable Entner-Doudoroff pathway in Z. mobilis requires only one-fourth the amount of enzymatic protein to sustain the same flux as the thermodynamically constrained pyrophosphate-dependent glycolytic pathway in C. thermocellum , with the Embden-Meyerhof-Parnas pathway in E. coli exhibiting intermediate thermodynamic favorability and enzyme demand. Across all three pathways, early reactions with stronger thermodynamic driving forces generally required lower enzyme investment than later, less favorable steps. Additionally, reflecting differences in glycolytic strategies, the highly reversible ethanol fermentation pathway in C. thermocellum requires 10-fold more protein to maintain the same flux as the irreversible, forward-driven ethanol fermentation pathway in Z. mobilis . Thus, protein investment across glycolytic pathways reflects differences in their thermodynamic favorability.

Clostridium thermocellum↗
DOE OSTI2025

Workflow for evaluating enzyme immobilization and performance for continuous flow manufacturing

Enzymes have shown promise in various industries due to their functional specificity, catalytic efficiency, and environmental sustainability. These biological catalysts can be a pivotal component of manufacturing pipelines like continuous flow chemistry. For this, there exists a need to robustly immobilize enzymes on solid supports and assess the effects of the solid supports on catalytic performance and stability. Here, we use an industrially relevant model enzyme, C. ensiformis (Jack bean) urease, to demonstrate immobilization and assess performance in the context of continuous flow manufacturing. Various immobilization strategies were screened focusing on immobilization efficiency, protocol simplicity, and urease biocatalyst kinetics. Based on this, CDI-agarose and NHS-agarose resins were identified as the best-performing immobilization strategies for urease. CDI-agarose-urease and NHS-agarose-urease were then scaled up and applied to a large-scale continuous flow reactor to evaluate product yields, operational stability, and long-term stability. These experiments identified differences in stability and performance depending on the immobilization method tested. This highlights the importance of screening immobilization methods and subsequent enzyme performance for each candidate biocatalyst used in manufacturing to promote optimal performance and stability. As such, this work provides a framework for evaluating enzyme biocatalyst immobilization approaches to improve performance and enable transition into industrial processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Combining Reactive Quantum-Mechanical Molecular-Dynamics Simulations with Mutagenesis, Crystallography, and Enzyme Kinetics to Reveal Plausible Steps of Isocyanide Hydratase Catalysis

A complete understanding of enzyme mechanisms requires atomistic details of chemical reactions. Quantum-based molecular dynamics simulations (QMD) are a potential source of this information, but trade-offs between accuracy and computational cost have limited their use. We previously developed extended Lagrangian Born–Oppenheimer molecular dynamics (XL-BOMD) methods that leverage a negligible compromise in accuracy to substantially decrease the cost of QMD simulations. Here, we develop a reactive QMD approach using the latest XL-BOMD formulation, which enables efficient simulations of highly reactive systems, and use it to investigate mechanisms of intermediate formation in isocyanide hydratase (ICH) catalysis. In QMD simulations, molecular analogs of ICH active site residues reacted with para-nitrophenyl isocyanide, forming a thioimidate. Analysis of simulated atomic configurational and charge dynamics revealed a pathway where protonation of the isocyanide carbon occurs prior to thioimidate formation and suggested a possible role of Asp17 as a proton donor in the early phase of ICH catalysis. To test whether the pathway seen using the reactive QMD approach might be relevant to ICH catalysis, we performed X-ray crystallography and pre-steady-state enzyme kinetics studies of wild-type and D17N mutant ICH. Both the structure and kinetics are sensitive to the D17N mutation in a manner that is consistent with the order of the reaction steps seen in the simulations. Mobile protons play essential roles in many enzymes, yet they are difficult to observe experimentally, making the ordering of proton-dependent steps ambiguous in many enzyme mechanisms. The ability to directly simulate model reactions for the design of experiments that provide information about enzyme mechanisms involving mobile protons demonstrates the significance of our reactive QMD approach and motivates further biological applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO2 Fluxes Upon Soil Warming

Abstract Understanding factors influencing carbon effluxes from soils to the atmosphere is important in a world experiencing climatic change. Two important uncertainties related to soil organic carbon (SOC) stock responses to a changing climate are (a) whether soil microbial communities acclimate or adapt to changes in soil temperature and (b) how to represent this process in SOC models. To further explore these issues, we included thermal adaptation of enzyme‐mediated processes in a mechanistic SOC model (ReSOM) using the macromolecular rate theory. Thermal adaptation is defined here to encompass all potential responses of soil microbes and microbial communities following a change in temperature. To assess the effects of thermal adaptation of enzyme‐mediated processes on simulated SOC losses, ReSOM was applied to data collected from a 13‐year soil warming experiment. Results show that a model omitting thermal adaptation of enzyme‐mediated processes substantially overestimates observed CO 2 effluxes during the initial years of soil warming. The bias against observed CO 2 effluxes was lower for models including thermal adaptation of enzyme‐mediated processes. In addition, for a simulated linear 3°C soil warming over 100 years, models including thermal adaptation of enzyme‐mediated processes simulated SOC losses of a factor of three smaller than models omitting this process. As thermal adaptation of microbial community characteristics is generally not included in models simulating feedback between the soil, biosphere and atmosphere, we encourage future studies to assess the potential impact that microbial adaptation has on soil carbon – climate feedback representations in models. Plain Language Summary A major uncertainty in projecting how much soil organic carbon (SOC) will be converted to CO 2 as a consequence of climate change is related to how soil microbes may adapt to increasing soil temperatures. While this “microbial thermal adaptation” has been shown to occur in short‐term lab incubation experiments, its effect on SOC cycling on a decadal timescale is not clear. To address this knowledge gap, a mechanistic SOC model was used to simulate data collected from a 13‐year soil warming experiment, to assess how microbial thermal adaptation affects predicted SOC losses upon soil warming. The model results show that incorporating microbial thermal adaptation into the model led to reduced CO 2 effluxes from the soil to the atmosphere compared to the common approach of omitting this mechanism. Our results imply that projected SOC losses for the decades to come may be reduced when this mechanism is incorporated in land models. We therefore advocate for more research on the mechanisms controlling microbial thermal adaptation, and how to implement this mechanism in SOC models. Key Points A crucial aspect of soil organic carbon (SOC) models is the representation of soil microbes Predicted soil CO 2 fluxes upon soil warming are reduced when accounting for microbial thermal adaptation On a centennial time scale, this thermal adaptation results in up to a factor of three lower predicted SOC loss

Van de Broek, Marijn↗
DOE OSTI2025

Unlocking soybean meal pectin recalcitrance using a multi-enzyme cocktail approach

Pectin is a complex plant heteropolysaccharide whose structure and function differ depending on its source. In animal feed, breaking down pectin is essential, as its presence increases feed viscosity and reduces nutrient absorption. Soybean meal, a protein-rich poultry feed ingredient, contains significant amounts of pectin, the structure of which remains unclear. Consequently, the enzyme activities required to degrade soybean meal pectin and how they interact are still open questions. In this study, we produced 15 recombinant fungal carbohydrate-active enzymes (CAZymes) identified from fungal secretomes acting on pectin. After observing that these enzymes were not active on soybean meal pectin when used alone, we developed a semi-miniaturized method to evaluate their effect as multi-activity cocktails. We designed and tested 12 enzyme pools, containing up to 15 different CAZymes, using several hydrolysis markers. Thanks to our multiactivity enzymatic approach combined with a Pearson correlation matrix, we identified 10 fungal CAZymes efficient on soybean meal pectin, 9 of which originate from Talaromyces versatilis. Based on enzyme specificity and linkage analysis, we propose a structural model for soybean meal pectin. Our findings underscore the importance of combining CAZymes to improve the degradation of agricultural co-products.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Machine learning prediction of enzyme optimum pH

The relationship between pH and enzyme catalytic activity, especially the optimal pH (pH opt ) at which enzymes function, is critical for biotechnological applications. Hence, computational methods to predict pH opt will enhance enzyme discovery and design by facilitating accurate identification of enzymes that function optimally at specific pH levels, and by elucidating sequence-function relationships. Here, in this study, we proposed and evaluated various machine learning methods for predicting pH opt , conducting extensive hyperparameter optimization and training over 11,000 model instances. Our results demonstrate that models utilizing language model embeddings markedly outperform other methods in predicting pHopt. We present EpHod, the best-performing model, to predict pHopt, making it publicly available to researchers. From sequence data, EpHod directly learns structural and biophysical features that relate to pH opt , including proximity of residues to the catalytic centre and the accessibility of solvent molecules. Overall, EpHod presents a promising advancement in pH opt prediction and will potentially speed up the development of enzyme technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

The anaerobic fungus Caecomyces churrovis produces H2 via a non-3 bifurcating NADH-dependent enzyme complex

Anaerobic fungi (AF) decompose lignocellulose-based biomass into fermentable sugars through the production of powerful biomass-degrading enzymes. AF are unusual among fungi in that they generate energy via hydrogenosomes, which are also associated with the release of H2 though yet unknown metabolic mechanisms. In particular, it remains unclear how NAD(P)+ is regenerated within hydrogenosomes and how H2 is formed. Here, we reveal the molecular mechanism for hydrogenosomal H2 production in the AF strain C. churrovis by combining genomic search, proteomic analysis, and enzymology. Our enzyme assays on the large organelle fraction of C. churrovis revealed the activity of H2:NAD+ oxidoreductase but not pyruvate:ferredoxin oxidoreductase activity. We identified genes encoding [FeFe] hydrogenase (Hyd) and NADH dehydrogenase subunits E and F (NuoE, NuoF) in C. churrovis, and confirmed their expression in the isolated hydrogenosomal fractions by proteomic analysis. Combining the individually purified proteins, we found that the assay system consisting of Hyd-Strep and NuoEF-Strep reduced NAD+ with H2. Furthermore, this system formed H2 directly from NADH independent of ferredoxin, functioning as a non-bifurcating NADH-dependent enzyme rather than an electron-bifurcating enzyme. We identified homologs of hydrogenosomal NuoE, NuoF, and Hyd in many other AF, indicating this pathway is widely conserved among the early-branching AF. This work demonstrates the existence of a non-bifurcating NADH-dependent enzyme complex in eukaryotes. Moreover, this complex could be a target for controlling AF H2 production and altering fungal metabolism.

fungi↗
DOE OSTI2025

Genetic and biochemical characterization of a radical SAM enzyme required for post-translational glutamine methylation of methyl-coenzyme M reductase

ABSTRACT Methyl-coenzyme M reductase (MCR), the key catalyst in the anoxic production and consumption of methane, contains an unusual 2-methylglutamine residue within its active site. In vitro data show that a B12-dependent radical SAM (rSAM) enzyme, designated MgmA, is responsible for this post-translational modification (PTM). Here, we show that two different MgmA homologs are able to methylate MCR in vivo when expressed in Methanosarcina acetivorans , an organism that does not normally possess this PTM. M. acetivorans strains expressing MgmA showed small, but significant, reductions in growth rates and yields on methylotrophic substrates. Structural characterization of the Ni(II) form of Gln-methylated M. acetivorans MCR revealed no significant differences in the protein fold between the modified and unmodified enzyme; however, the purified enzyme contained the heterodisulfide reaction product, as opposed to the free cofactors found in eight prior M. acetivorans MCR structures, suggesting that substrate/product binding is altered in the modified enzyme. Structural characterization of MgmA revealed a fold similar to other B12-dependent rSAMs, with a wide active site cleft capable of binding an McrA peptide in an extended, linear conformation. IMPORTANCE Methane plays a key role in the global carbon cycle and is an important driver of climate change. Because MCR is responsible for nearly all biological methane production and most anoxic methane consumption, it plays a major role in setting the atmospheric levels of this important greenhouse gas. Thus, a detailed understanding of this enzyme is critical for the development of methane mitigation strategies.

Rodriguez Carrero, Roy J. (ORCID:0000000184475641)↗
DOE OSTI2024

Crystallographic Fragment Screening of a Bifunctional Proline Catabolic Enzyme Reveals New Inhibitor Templates for Proline Dehydrogenase and L-Glutamate-γ-semialdehyde Dehydrogenase

The proline catabolic pathway consisting of proline dehydrogenase (PRODH) and L-glutamate-γ-semialdehyde (GSAL) dehydrogenase (GSALDH) catalyzes the four-electron oxidation of L-proline to L-glutamate. Chemical probes to these enzymes are of interest for their role in cancer and inherited metabolic disease. Here, we report the results of a crystallographic fragment-screening campaign targeting both enzymes. A unique aspect of our approach is the screening of both enzymes simultaneously using crystals of the bifunctional PRODH-GSALDH enzyme, proline utilization A (PutA). A 288-fragment library from Zenobia was screened in crystallo in cocktails of six fragments. Validation X-ray crystallography with individual fragments identified seven crystal hits distributed in the PRODH active site, GSALDH aldehyde substrate-binding site, and GSALDH NAD+ adenine-binding site. The fragment bound in the PRODH active site, 4-methoxybenzyl alcohol, is structurally distinct from all known PRODH inhibitors as it lacks an anionic anchor and stabilizes open conformations of the active site, motivating the study of eighteen analogs. In total, thirteen crystal structures with resolutions ranging from 1.32 Å to 1.80 Å were determined, resolving the poses and interactions of seven fragments from the Zenobia library and five analogs of 4-methoxybenzyl alcohol. These results expand the chemical space of probes targeting proline catabolic enzymes and provide new structural information for further inhibitor development.

Biochemistry & Molecular Biology↗
NASA NTRS1971

Insolubilization process increases enzyme stability

Enzymes complexed with polymeric matrices contain properties suggesting application to enzyme-controlled reactions. Stability of insolubilized enzyme derivatives is markedly greater than that of soluble enzymes and physical form of insolubilized enzymes is useful in column and batch processes.

Billingham, J.↗
NASA NTRS1995

A DNA enzyme with Mg(2+)-Dependent RNA Phosphoesterase Activity

Previously we demonstrated that DNA can act as an enzyme in the Pb(2+)-dependent cleavage of an RNA phosphoester. This is a facile reaction, with an uncatalyzed rate for a typical RNA phosphoester of approx. 10(exp -4)/ min in the presence of 1 mM Pb(OAc)2 at pH 7.0 and 23 C. The Mg(2+) - dependent reaction is more difficult, with an uncatalyzed rate of approx. 10(exp -7)/ min under comparable conditions. Mg(2+) - dependent cleavage has special relevance to biology because it is compatible with intracellular conditions. Using in vitro selection, we sought to develop a family of phosphoester-cleaving DNA enzymes that operate in the presence of various divalent metals, focusing particularly on the Mg(2+) - dependent reaction. Results: We generated a population of greater than 10(exp 13) DNAs containing 40 random nucleotides and carried out repeated rounds of selective amplification, enriching for molecules that cleave a target RNA phosphoester in the presence of 1 mM Mg(2+), Mn(2+), Zn(2+) or Pb(2+). Examination of individual clones from the Mg(2+) lineage after the sixth round revealed a catalytic motif comprised of a three-stem junction.This motif was partially randomized and subjected to seven additional rounds of selective amplification, yielding catalysts with a rate of 0.01/ min. The optimized DNA catalyst was divided into separate substrate and enzyme domains and shown to have a similar level of activity under multiple turnover conditions. Conclusions: We have generated a Mg(2+) - dependent DNA enzyme that cleaves a target RNA phosphoester with a catalytic rate approx. 10(exp 5) - fold greater than that of the uncatalyzed reaction. This activity is compatible with intracellular conditions, raising the possibility that DNA enzymes might be made to operate in vivo.

Breaker, Ronald R.↗