Testing for the ability to modify antibiotics of Panus tigrinus 8/18 Lentinus strigosus 1566 laccase / Teste de capacidade para modificar antibióticos a partir da lacase de Panus tigrinus 8/18 e Lentinus strigosus 1566

In advanced biotechnology, the utilization of enzymes to achieve new or modified compounds with antibacterial, fungicidal, and anti-cancer specifications is crucial. Mushroom lactases are a hopeful biocatalyst for the synthesis and modification of different compounds. They are an accessible and inexpensive enzyme for the preparation of reaction objects and have recently received attention. Laccase purification was performed from basidiomycete Lentinus strigosus (LS) in several stages: Stage 1. On ion-exchange chromatography on TEAE Servacell 23 (400 ml), two distinctly separated laccase activity peaks were observed, eluted from the carrier at 0.21 and 0.27 M NaCl. In order to reduce the loss of enzymes, all fractions with laccase activity were collected, concentrated, and desalted using an ultrafiltration cell (Amicon, United States) with a UM-10 membrane. Stage 2. The resulting preparation with laccase activity was applied to a Q-Sepharose column (60 ml). Two well-separated peaks with laccase activity were obtained during the elution: laccase I (0.12 M NaCl) and laccase II (0.2 M NaCl). Stage 3. In the course of further purification of both enzymes, carried out on anion-exchange carrier Resource Q (6 ml), a broken gradient was used: 0 - 10%, 10 - 20%, and 20 - 100% with 1M NaCl. Stage 4. Both laccase I and laccase II, obtained after Resource Q, were desalted, concentrated to 1 ml each, and applied to a Superdex 75 gel filtration column. As a result, two laccases were obtained in a homogeneous form.

Na biotecnologia moderna, o uso de enzimas para obter compostos novos ou modificados com propriedades antibacterianas, antifúngicas e anticancerígenas é crucial. Lactases de cogumelos são biocatalisadores promissores para síntese e modificação de diferentes compostos, por serem enzimas baratas e disponíveis para a preparação de componentes de reação, e vem recebendo a devida atenção recentemente. A purificação da lacase foi realizada a partir do basidiomiceto Lentinus strigosus em vários estágios: Etapa 1 - na cromatografia de troca iônica em TEAE Servacell 23 (400 ml), foram observados dois picos de atividade da lacase distintamente separados, com eluição do transportador a 0,21 e 0,27 M de NaCl. Para reduzir a perda de enzimas, todas as frações com atividade de lacase foram coletadas, concentradas e dessalinizadas em uma célula de ultrafiltração (Amicon, Estados Unidos) com membrana UM-10; Etapa 2 - a preparação resultante com atividade de lacase foi aplicada a uma coluna Q-Sepharose (60 ml). Durante a eluição, foram obtidos dois picos bem separados com atividade de lacase: lacase I (NaCl 0,12 M) e lacase II (NaCl 0,2 M); Etapa 3 - no decurso da purificação adicional de ambas as enzimas, realizada no Recurso Q de transportador de troca aniônica (6 ml), um gradiente quebrado foi usado: 0-10%, 10-20% e 20-100% com NaCl 1M; Etapa 4 - tanto a lacase I como a lacase II, obtidas após o Recurso Q, foram dessalinizadas e concentradas para 1 ml cada e aplicadas a uma coluna de filtração em gel Superdex 75. Como resultado, duas lacases foram obtidas de forma homogênea.

How Flexibility Can Enhance Catalysis.

Conformational changes are observed in many enzymes, but their role in catalysis is highly controversial. Here we present a theoretical model that illustrates how rigid catalysts can be fundamentally limited and how a conformational change induced by substrate binding can overcome this limitation, ultimately enabling barrier-free catalysis. The model is deliberately minimal, but the principle it illustrates is general and consistent with unique features of proteins as well as with previous informal proposals to explain the superiority of enzymes over other classes of catalysts. Implementing the discriminative switch suggested by the model could help overcome limitations currently encountered in the design of artificial catalysts.

Recent advances in the synthesis and applications of single-atom nanozymes in food safety monitoring.

Nanozymes are synthetic compounds with enzyme-like tunable catalytic properties. The success of nanozymes for catalytic applications can be attributed to their small dimensions, cost-effective synthesis, appreciable stability, and scalability to molecular dimensions. The emergence of single atom nanozymes (SANzymes) has opened up new possibilities in bioanalytical applications. In this regard, this review outlines enzyme-mimicking features of SANzymes for food safety applications in relation to the key variables controlling their catalytic performance. The discussion is extended further to cover the applications of SANzymes for the monitoring of various compounds/biomaterials of significance with respect to food safety (e.g., pesticides, veterinary drug residues, foodborne pathogenic bacteria, mycotoxins/bacterial endotoxin, antioxidant residues, hydrogen peroxide residues, and heavy metal ions). Furthermore, the performance of SANzymes is evaluated in terms of various performance metrics such as limit of detection (LOD), linear dynamic range, and figure of merit (FoM). The challenges and future road map for the applications of SANzymes are also addressed along with their upscaling in the area of food safety.

Endophytic bacteria isolated from Urtica dioica L.- preliminary screening for enzyme and polyphenols production.

Endophytes, especially those isolated from herbal plants, may act as a reservoir of a variety of secondary metabolites exhibiting biological activity. Some endophytes express the ability to produce the same bioactive compounds as their plant hosts, making them a more sustainable industrial supply of these substances. Urtica dioica L. (common stinging nettle) is a synanthropic plant that is widely used in herbal medicine due to the diversity of bioactive chemicals it contains, e.g., polyphenols, which demonstrate anti-inflammatory, antioxidant, and anti-cancerous capabilities. This study aimed at isolating endophytic bacteria from stinging nettles for their bioactive compounds. The endophytic isolates were identified by both biochemical and molecular methods (16S rRNA) and investigated for enzymes, biosurfactants, and polyphenols production. Each of the isolated bacterial strains was capable of producing biosurfactants and polyphenols. However, three of the isolated endophytes, identified as two strains of Bacillus cereus and one strain of Bacillus mycoides, possessed the greatest capacity to produce biosurfactants and polyphenols. The derivatized extracts from culture liquid showed the 1.633 mol l-1 (9.691 mg l-1) concentration of polyphenol compounds. Therefore, the present study signifies that endophytic B. cereus and B. mycoides isolated from Urtica dioica L. could be a potential source of biosurfactants and polyphenols. However, further study is required to understand the mechanism of the process and achieve efficient polyphenol production by endophytic bacteria.

Cold-adapted enzymes: mechanisms, engineering and biotechnological application.

Most cold-adapted enzymes display high catalytic activity at low temperatures (20-25 °C) and can still maintain more than 40-50% of their maximum activity at lower temperatures (0-10 °C) but are inactivated after a moderate increase in temperature. The activity of some cold-adapted enzymes increases significantly in the presence of high salt concentrations and metal ions. Interestingly, we also observed that some cold-adapted enzymes have a wide range of optimum temperatures, exhibiting not only maximum activity under low-temperature conditions but also the ability to maintain high enzyme activity under high-temperature conditions, which is a novel feature of cold-adapted enzymes. This unique property of cold-adapted enzymes is generally attractive for biotechnological and industrial applications because these enzymes can reduce energy consumption and the chance of microbial contamination, thereby lowering the production costs and maintaining the flavor, taste and quality of foods. How high catalytic activity is maintained at low temperatures remains unknown. The relationship between the structure of cold-adapted enzymes and their activity, flexibility and stability is complex, and thus far, a unified explanation has not been provided. Herein, we systematically review the sources, catalytic characteristics and cold adaptation of enzymes from four enzymes categories systematically and discuss how these properties may be exploited in biotechnology. A thorough understanding of the properties, catalytic mechanisms, and engineering of cold-adapted enzymes is critical for future biotechnological applications in the detergent industry and food and beverage industries.

Control analysis in the identification of key enzymes driving metabolic adaptations: Towards drug target discovery.

Metabolic Control Analysis (MCA) marked a turning point in understanding the design principles of metabolic network control by establishing control coefficients as a means to quantify the degree of control that an enzyme exerts on flux or metabolite concentrations. MCA has demonstrated that control of metabolic pathways is distributed among many enzymes rather than depending on a single rate-limiting step. MCA also proved that this distribution depends not only on the stoichiometric structure of the network but also on other kinetic determinants, such as the degree of saturation of the enzyme active site, the distance to thermodynamic equilibrium, and metabolite feedback regulatory loops. Consequently, predicting the alterations that occur during metabolic adaptation in response to strong changes involving a redistribution in such control distribution can be challenging. Here, using the framework provided by MCA, we illustrate how control distribution in a metabolic pathway/network depends on enzyme kinetic determinants and to what extent the redistribution of control affects our predictions on candidate enzymes suitable as targets for small molecule inhibition in the drug discovery process. Our results uncover that kinetic determinants can lead to unexpected control distribution and outcomes that cannot be predicted solely from stoichiometric determinants. We also unveil that the inference of key enzyme-drivers of an observed metabolic adaptation can be dramatically improved using mean control coefficients and ruling out those enzyme activities that are associated with low control coefficients. As the use of constraint-based stoichiometric genome-scale metabolic models (GSMMs) becomes increasingly prevalent for identifying genes/enzymes that could be potential drug targets, we anticipate that incorporating kinetic determinants and ruling out enzymes with low control coefficients into GSMM workflows will facilitate more accurate predictions and reveal novel therapeutic targets.

EFI-EST, EFI-GNT, and EFI-CGFP: Enzyme Function Initiative (EFI) Web Resource for Genomic Enzymology Tools.

The Enzyme Function Initiative (EFI) provides a web resource with "genomic enzymology" web tools to leverage the protein (UniProt) and genome (European Nucleotide Archive; ENA; https://www.ebi.ac.uk/ena/) databases to assist the assignment of in vitro enzymatic activities and in vivo metabolic functions to uncharacterized enzymes (https://efi.igb.illinois.edu/). The tools enable (1) exploration of sequence-function space in enzyme families using sequence similarity networks (SSNs; EFI-EST), (2) easy access to genome context for bacterial, archaeal, and fungal proteins in the SSN clusters so that isofunctional families can be identified and their functions inferred from genome context (EFI-GNT); and (3) determination of the abundance of SSN clusters in NIH Human Metagenome Project metagenomes using chemically guided functional profiling (EFI-CGFP). We describe enhancements that enable SSNs to be generated from taxonomy categories, allowing higher resolution analyses of sequence-function space; we provide examples of the generation of taxonomy category-specific SSNs.

Rank-ordering of known enzymes as starting points for re-engineering novel substrate activity using a convolutional neural network.

Retro-biosynthetic approaches have made significant advances in predicting synthesis routes of target biofuel, bio-renewable or bio-active molecules. The use of only cataloged enzymatic activities limits the discovery of new production routes. Recent retro-biosynthetic algorithms increasingly use novel conversions that require altering the substrate or cofactor specificities of existing enzymes while connecting pathways leading to a target metabolite. However, identifying and re-engineering enzymes for desired novel conversions are currently the bottlenecks in implementing such designed pathways. Herein, we present EnzRank, a convolutional neural network (CNN) based approach, to rank-order existing enzymes in terms of their suitability to undergo successful protein engineering through directed evolution or de novo design towards a desired specific substrate activity. We train the CNN model on 11,800 known active enzyme-substrate pairs from the BRENDA database as positive samples and data generated by scrambling these pairs as negative samples using substrate dissimilarity between an enzyme's native substrate and all other molecules present in the dataset using Tanimoto similarity score. EnzRank achieves an average recovery rate of 80.72% and 73.08% for positive and negative pairs on test data after using a 10-fold holdout method for training and cross-validation. We further developed a web-based user interface (available at https://huggingface.co/spaces/vuu10/EnzRank) to predict enzyme-substrate activity using SMILES strings of substrates and enzyme sequence as input to allow convenient and easy-to-use access to EnzRank. In summary, this effort can aid de novo pathway design tools to prioritize starting enzyme re-engineering candidates for novel reactions as well as in predicting the potential secondary activity of enzymes in cell metabolism.

Bioengineered Enzymes and Precision Fermentation in the Food Industry.

Enzymes have been used in the food processing industry for many years. However, the use of native enzymes is not conducive to high activity, efficiency, range of substrates, and adaptability to harsh food processing conditions. The advent of enzyme engineering approaches such as rational design, directed evolution, and semi-rational design provided much-needed impetus for tailor-made enzymes with improved or novel catalytic properties. Production of designer enzymes became further refined with the emergence of synthetic biology and gene editing techniques and a plethora of other tools such as artificial intelligence, and computational and bioinformatics analyses which have paved the way for what is referred to as precision fermentation for the production of these designer enzymes more efficiently. With all the technologies available, the bottleneck is now in the scale-up production of these enzymes. There is generally a lack of accessibility thereof of large-scale capabilities and know-how. This review is aimed at highlighting these various enzyme-engineering strategies and the associated scale-up challenges, including safety concerns surrounding genetically modified microorganisms and the use of cell-free systems to circumvent this issue. The use of solid-state fermentation (SSF) is also addressed as a potentially low-cost production system, amenable to customization and employing inexpensive feedstocks as substrate.

Optimal enzyme utilization suggests that concentrations and thermodynamics determine binding mechanisms and enzyme saturations.

Deciphering the metabolic functions of organisms requires understanding the dynamic responses of living cells upon genetic and environmental perturbations, which in turn can be inferred from enzymatic activity. In this work, we investigate the optimal modes of operation for enzymes in terms of the evolutionary pressure driving them toward increased catalytic efficiency. We develop a framework using a mixed-integer formulation to assess the distribution of thermodynamic forces and enzyme states, providing detailed insights into the enzymatic mode of operation. We use this framework to explore Michaelis-Menten and random-ordered multi-substrate mechanisms. We show that optimal enzyme utilization is achieved by unique or alternative operating modes dependent on reactant concentrations. We find that in a bimolecular enzyme reaction, the random mechanism is optimal over any other ordered mechanism under physiological conditions. Our framework can investigate the optimal catalytic properties of complex enzyme mechanisms. It can further guide the directed evolution of enzymes and fill in the knowledge gaps in enzyme kinetics.

Curse and Blessing of Non-Proteinogenic Parts in Computational Enzyme Engineering.

Enzyme engineering aims to improve or install a new function in biocatalysts for applications ranging from chemical synthesis to biomedicine. For decades, computational techniques have been developed to predict the effect of protein changes and design new enzymes. However, these techniques may have been optimized to deal with proteins composed of the standard amino acid alphabet, while the function of many enzymes relies on non-proteogenic parts like cofactors, nucleic acids, and post-translational modifications. Enzyme systems containing such molecules might be handled or modeled improperly by computational tools, and thus be unsuitable, or require additional tweaking, parameterization, or preparation. In this review, we give an overview of common and recent tools and workflows available to computational enzyme engineers. We highlight the various pitfalls that come with including non-proteogenic compounds in computations and outline potential ways to address common issues. Finally, we showcase successful examples from the literature that computationally engineered such enzymes.

Unravelling the complexity of enzyme catalysis.

The study of enzymes never disappoints. Despite its long history-almost 150 years following the first documented use of the word enzyme in 1878-the field of enzymology advances apace. This long journey has witnessed landmark developments that have defined modern enzymology as a broad discipline, leading to improved understanding at the molecular level, as we aspire to discover the complex relationships between enzyme structures, catalytic mechanisms and biological function. How enzymes are regulated at the gene and post-translational levels and how catalytic activity is modulated by interactions with small ligands and macromolecules, or the broader enzyme environment, are topical areas of study. Insights from such studies guide the exploitation of natural and engineered enzymes in biomedical or industrial processes; for example, in diagnostics, pharmaceuticals manufacture and processing technologies that use immobilised enzymes and enzyme reactor-based systems. In this Focus Issue, The FEBS Journal seeks to highlight breaking science and informative reviews, as well as personal reflections, to illustrate the breadth and importance of contemporary molecular enzymology research.

Psychrophilic enzymes: strategies for cold-adaptation.

Psychrophilic organisms thriving at near-zero temperatures synthesize cold-adapted enzymes to sustain cell metabolism. These enzymes have overcome the reduced molecular kinetic energy and increased viscosity inherent to their environment and maintained high catalytic rates by development of a diverse range of structural solutions. Most commonly, they are characterized by a high flexibility coupled with an intrinsic structural instability and reduced substrate affinity. However, this paradigm for cold-adaptation is not universal as some cold-active enzymes with high stability and/or high substrate affinity and/or even an unaltered flexibility have been reported, pointing to alternative adaptation strategies. Indeed, cold-adaptation can involve any of a number of a diverse range of structural modifications, or combinations of modifications, depending on the enzyme involved, its function, structure, stability, and evolutionary history. This paper presents the challenges, properties, and adaptation strategies of these enzymes.

Halomonas elongata: a microbial source of highly stable enzymes for applied biotechnology.

Extremophilic microorganisms, which are resistant to extreme levels of temperature, salinity, pH, etc., have become popular tools for biotechnological applications. Due to their availability and cost-efficacy, enzymes from extremophiles are getting the attention of researchers and industries in the field of biocatalysis to catalyze diverse chemical reactions in a selective and sustainable manner. In this mini-review, we discuss the advantages of Halomonas elongata as moderate halophilic bacteria to provide suitable enzymes for biotechnology. While enzymes from H. elongata are more resistant to the presence of salt compared to their mesophilic counterparts, they are also easier to produce in heterologous hosts compared with more extremophilic microorganisms. Herein, a set of different enzymes (hydrolases, transferases, and oxidoreductases) from H. elongata are showcased, highlighting their interesting properties as more efficient and sustainable biocatalysts. With this, we aim to improve the visibility of halotolerant enzymes and their uncommon properties to integrate biocatalysis in industrial set-ups. KEYPOINTS: • Production and use of halotolerant enzymes can be easier than strong halophilic ones. • Enzymes from halotolerant organisms are robust catalysts under harsh conditions. • Halomonas elongata has shown a broad enzyme toolbox with biotechnology applications.

Carbohydrate-active enzymes in animal feed.

Considering an ever-growing global population, which hit 8 billion people in the fall of 2022, it is essential to find solutions to avoid the competition between human food and animal feed for croplands. Agricultural co-products have become important components of the circular economy with their use in animal feed. Their implementation was made possible by the addition of exogenous enzymes in the diet, especially carbohydrate-active enzymes (CAZymes). In this review, we describe the diversity and versatility of microbial CAZymes targeting non-starch polysaccharides to improve the nutritional potential of diets containing cereals and protein meals. We focused our attention on cellulases, hemicellulases, pectinases which were often found to be crucial in vivo. We also highlight the performance and health benefits brought by the exogenous addition of enzymatic cocktails containing CAZymes in the diets of monogastric animals. Taking the example of the well-studied commercial cocktail Rovabio™, we discuss the evolution, constraints and future challenges faced by feed enzymes suppliers. We hope that this review will promote the use and development of enzyme solutions for industries to sustainably feed humans in the future.

Enzymes and Enzyme Inhibitors-Applications in Medicine and Diagnosis.

This is the first part of a Special Issue on enzymes and enzymes inhibitors and their applications in medicine and diagnosis [...].

Protein Dynamics and Enzymatic Catalysis.

This Perspective presents a review of our work and that of others in the highly controversial topic of the coupling of protein dynamics to reaction in enzymes. We have been involved in studying this topic for many years. Thus, this perspective will naturally present our own views, but it also is designed to present an overview of the variety of viewpoints of this topic, both experimental and theoretical. This is obviously a large and contentious topic.

Solvent tolerant enzymes in extremophiles: Adaptations and applications.

Non-aqueous enzymology has always drawn attention due to the wide range of unique possibilities in biocatalysis. In general, the enzymes do not or insignificantly catalyze substrate in the presence of solvents. This is due to the interfering interactions of the solvents between enzyme and water molecules at the interface. Therefore, information about solvent-stable enzymes is scarce. Yet, solvent-stable enzymes prove quite valuable in the present day biotechnology. The enzymatic hydrolysis of the substrates in solvents synthesizes commercially valuable products, such as peptides, esters, and other transesterification products. Extremophiles, the most valuable yet not extensively explored candidates, can be an excellent source to investigate this avenue. Due to inherent structural attributes, many extremozymes can catalyze and maintain stability in organic solvents. In the present review, we aim to consolidate information about the solvent-stable enzymes from various extremophilic microorganisms. Further, it would be interesting to learn about the mechanism adapted by these microorganisms to sustain solvent stress. Various approaches to protein engineering are used to enhance catalytic flexibility and stability and broaden biocatalysis's prospects under non-aqueous conditions. It also describes strategies to achieve optimal immobilization with minimum inhibition of the catalysis. The proposed review would significantly aid our understanding of non-aqueous enzymology.

Enzyme function prediction using contrastive learning.

Enzyme function annotation is a fundamental challenge, and numerous computational tools have been developed. However, most of these tools cannot accurately predict functional annotations, such as enzyme commission (EC) number, for less-studied proteins or those with previously uncharacterized functions or multiple activities. We present a machine learning algorithm named CLEAN (contrastive learning-enabled enzyme annotation) to assign EC numbers to enzymes with better accuracy, reliability, and sensitivity compared with the state-of-the-art tool BLASTp. The contrastive learning framework empowers CLEAN to confidently (i) annotate understudied enzymes, (ii) correct mislabeled enzymes, and (iii) identify promiscuous enzymes with two or more EC numbers-functions that we demonstrate by systematic in silico and in vitro experiments. We anticipate that this tool will be widely used for predicting the functions of uncharacterized enzymes, thereby advancing many fields, such as genomics, synthetic biology, and biocatalysis.