Free energy analysis of ω-transaminase reactions to dissect how the enzyme controls the substrate selectivity

Mannosidase-inhibiting iminosugar production by recombinant Corynebacterium glutamicum harboring the 1-deoxynojirimycin biosynthetic gene cluster

The iminosugar class of carbohydrate-active enzyme inhibitors has therapeutic applications in metabolic syndrome conditions, viral infections and cancer. Compared to chemical synthesis, microbial iminosugar production has benefits of cost, sustainability and optimization. In this study, the 1-deoxynojirimycin (DNJ) biosynthetic gene cluster from Bacillus velezensis MBLB0692, and its individual genes, were cloned into Corynebacterium glutamicum (Cg). Characterizations of the encoded aminotransferase GabT1, phosphatase Yktc1, and dehydrogenase GutB1, were performed with purified enzymes and whole cell biocatalysts bearing individual and clustered (TYB) genes. GabT1 showed a variable pattern in its half-reaction with a slow turnover. GutB1 was an alkaline dehydrogenase with a broad substrate specificity and no divalent ion dependency while the zinc-dependent phosphatase Yktc1 had substrate specificity that was both pH- and ion-dependent. The CgYktc1 and CgGutB1 whole cells were viable biocatalysts with wider ranges of substrates than their enzyme counterparts. The CgTYB cells produced mannosidase-inhibiting iminosugars corresponding to mannojirimycin dehydrate (162 m/z) and deoxymannojirimycin (164 m/z). Mannosidase inhibitors have been found to be effective in treating orphan diseases, cancer and viral infections, and their biosynthesis by recombinant C. glutamicum can be optimized for industrial production and novel drug development.

Artificial neural networks in the modeling of the catalytic activity of a biosensor composed of conjugated polymers and urease

Thin films of conjugated polymer and enzyme can be used to unravel the interaction between components in a biosensor. Using artificial neural networks (ANNs) improves data interpretability and helps construct models with great capacity for classifying and processing information. The present work used kinetic data from the catalytic activity of urease immobilized in different conjugated polymers to create ANN models using time, substrate concentration, and absorbance as input variables since the models had absorbance in a posterior instant as output value to explore the predictivity of the ANNs. The performance of the models was evaluated by Pearson's correlation coefficient (ρ) and mean squared error (MSE) values. After the learning process, a series of new experiments were performed to verify the generality of the models. As the main results, the best ANN model presented 0.9980 and 3.0736 × 10-5 for ρ and MSE, respectively. For the simulation step, intermediary values of substrate concentration were used. The mean absolute percentage error (MAPE) values were 3.34, 3.07, and 3.78 for 12 mM, 22 mM, and 32 mM concentrations, respectively. Overall, with the simulations, it was possible to ascertain the interpolatory capacity of the model, which has a learning mechanism based on absorbance and time as variables. Thus, the potential of ANNs would be in their use in pre-evaluations, helping to determine the substrate concentration at which there is higher catalytic activity or in determining the linear range of the sensor.

Biochemical characterization and synthetic application of aromatic L-amino acid decarboxylase from Bacillus atrophaeus

Aromatic L-amino acid decarboxylases (AADCs) are ubiquitously found in higher organisms owing to their physiological role in the synthesis of neurotransmitters and alkaloids. However, bacterial AADC has not attracted much attention because of its rather limited availability and narrow substrate range. Here, we examined the biochemical properties of AADC from Bacillus atrophaeus (AADC-BA) and assessed the synthetic feasibility of the enzyme for the preparation of monoamine neurotransmitters. AADC-BA was expressed in Escherichia coli BL21(DE3) and the purified enzyme showed a specific activity of 2.6 ± 0.4 U/mg for 10 mM L-phenylalanine (L-Phe) at 37 °C. AADC-BA showed optimal pH and temperature ranges at 7-8 and 37-45 °C, respectively. The K_M and k_cat values for L-Phe were 7.2 mM and 7.4 s^-1, respectively, at pH 7.0 and 37 °C. Comparison of the kinetic constants at different temperatures revealed that the temperature dependency of the enzyme was mainly determined by catalytic turnover rather than substrate binding. AADC-BA showed a broad substrate scope for various aromatic amino acids, including L-Phe, L-tryptophan (610% relative to L-Phe), L-tyrosine (12%), 3,4-dihydroxyphenyl-L-alanine (24%), 5-hydroxy-L-tryptophan (L-HTP, 71%), 4-chloro-L-phenylalanine (520%), and 4-nitro-L-phenylalanine (450%). Homology modeling and docking simulations were carried out and were consistent with the observed substrate specificity. To demonstrate the synthetic potential of AADC-BA, we carried out the production of serotonin by decarboxylation of L-HTP. The reaction yield of serotonin reached 98% after 1 h at the reaction conditions of 50 mM L-HTP and 4 U/mL AADC-BA. Moreover, we carried out preparative-scale decarboxylation of L-Phe (100 mM in 40-mL reaction mixture) and isolated the resulting 2-phenylethylamine (51% recovery yield). We expect that the broad substrate specificity of AADC-BA can be exploited to produce various aromatic biogenic amines. KEY POINTS: • AADC-BA showed broad substrate specificity for various aromatic amino acids. • The substrate specificity was elucidated by in silico structural modeling. • The synthetic potential of AADC-BA was demonstrated for the production of biogenic amines.

Mapping enzyme-substrate interactions: its potential to study the mechanism of enzymes

With the increase of the need to use more sustainable processes for the industry in our society, the modeling of enzymes has become crucial to fully comprehend their mechanism of action and use this knowledge to enhance and design their properties. A lot of methods to study enzymes computationally exist and they have been classified on sequence-based, structure-based, and the more new artificial intelligence-based ones. Albeit the abundance of methods to help predict the function of an enzyme, molecular modeling is crucial when trying to understand the enzyme mechanism, as they aim to correlate atomistic information with experimental data. Among them, methods that simulate the system dynamics at a molecular mechanics level of theory (classical force fields) have shown to offer a comprehensive study. In this book chapter, we will analyze these techniques, emphasizing the importance of precise modeling of enzyme-substrate interactions. In the end, a brief explanation of the transference of the information from research studies to the industry is given accompanied with two examples of family enzymes where their modeling has helped their exploitation.

Characterization of a novel thermostable (S)-amine-transaminase from an Antarctic moderately-thermophilic bacterium Albidovulum sp. SLM16

Amine-transaminases (ATAs) are enzymes that catalyze the reversible transfer of an amino group between primary amines and carbonyl compounds. They have been widely studied in the last decades for their application in stereoselective synthesis of chiral amines, which are one of the most valuable building blocks in pharmaceuticals manufacturing. Their excellent enantioselectivity, use of low-cost substrates and no need for external cofactors has turned these enzymes into a promising alternative to the chemical synthesis of chiral amines. Nevertheless, its application at industrial scale remains limited mainly because most of the available ATAs are scarcely tolerant to harsh reaction conditions such as high temperatures and presence of organic solvents. In this work, a novel (S)-ATA was discovered in a thermophilic bacterium, Albidovulum sp. SLM16, isolated from a geothermal Antarctic environmental sample, more specifically from a shoreline fumarole in Deception Island. The transaminase-coding gene was identified in the genome of the microorganism, cloned and overexpressed in Escherichia coli for biochemical characterization. The activity of the recombinant ATA was optimal at 65 °C and pH 9.5. Molecular mass estimates suggest a 75 kDa homodimeric structure. The enzyme turned out to be highly thermostable, maintaining 80% of its specific activity after 5 days of incubation at 50 °C. These results indicate that ATA_SLM16 is an excellent candidate for potential applications in biocatalytic synthesis. To the best of our knowledge, this would be the first report of the characterization of a thermostable (S)-ATA discovered by means of in vivo screening of thermophilic microorganisms.

Asymmetric synthesis of l-phosphinothricin using thermostable alpha-transaminase mined from Citrobacter koseri

α-Transaminase (α-TA) responsible for catalyzing the reversible transfer of amino groups between amine donors and amine acceptors, is applicable to enzymatic route for asymmetric synthesis of herbicide l-phosphinothricin (l-PPT). In the search for α-TAs with better catalysis performance, three α-TAs were discovered by genome mining approach using a known sequence encoding Escherichia coli tyrosine TA (TyrB) as probe. Through detailed comparison of their expression amount, activities and characteristics, Citrobacter koseri TA (CkTA) exhibited better activity and thermostability, which retain 65.9% of initial activity after incubation at 57 °C for 4 h. The K_m and k_cat/K_m values of CkTA were 36.75 mM and 34.29 mM^-1 min^-1, respectively. In addition, recombinant CkTA cells were immobilized onto Celite 545 using tris(hydroxymethyl)phosphine as crosslinker. During five repetitive asymmetric synthesis of l-PPT from 20 g/L prostereogenic ketone using l-Glu as amine donor, all the yields of l-PPT reached up to 91.2% (＞99% ee). These characteristics made CkTA a valuable addition to the currently scarce α-TA library for stereospecific synthesis of l-PPT.

Application of ω-Transaminases in the Pharmaceutical Industry

Chiral amines are valuable building blocks for the pharmaceutical industry. ω-TAms have emerged as an exciting option for their synthesis, offering a potential "green alternative" to overcome the drawbacks associated with conventional chemical methods. In this review, we explore the application of ω-TAms for pharmaceutical production. We discuss the diverse array of reactions available involving ω-TAms and process considerations of their use in both kinetic resolution and asymmetric synthesis. With the aid of specific drug intermediates and APIs, we chart the development of ω-TAms using protein engineering and their contribution to elegant one-pot cascades with other enzymes, including carbonyl reductases (CREDs), hydrolases and monoamine oxidases (MAOs), providing a comprehensive overview of their uses, beginning with initial applications through to the present day.

Spectrophotometric assay for sensitive detection of glycerol dehydratase activity using aldehyde dehydrogenase

Glycerol dehydratase (GDHt) is a pivotal enzyme for fermentative utilization of glycerol by catalyzing radical-mediated conversion of glycerol into 3-hydroxypropionaldehyde (3-HPA). Precise and sensitive monitoring of cellular GDHt activity during the fermentation process is a prerequisite for reliable metabolic analysis to afford efficient cellular engineering and process optimization. Here we report a new spectrophotometric assay for the sensitive measurement of the GDHt activity with a sub-nanomolar limit of detection (LOD). The assay method employs aldehyde dehydrogenase (ALDH) as a reporter enzyme, so the readout of the GDHt activity is recorded at 340 nm as an increase in UV absorbance which results from NADH generation accompanied by oxidation of 3-HPA to 3-hydroxypropionic acid (3-HP). The GDHt assay was performed under the reaction conditions where the ALDH activity overwhelms the GDHt activity (i.e., 50-fold higher activity of ALDH relative to GDHt activity), affording sensitive detection of GDHt with 360 pM LOD. The ALDH-coupled assay was used to determine kinetic parameters of GDHt for glycerol, leading to K_M = 0.73 ± 0.09 mM and k_cat = 400 ± 20 s^-1 which are in reasonable agreements with the previous reports. Our assay method allowed measurement of even a 10⁴-fold decrease in the cellular GDHt activity during fermentative production of 3-HP, which demonstrates the detection sensitivity much higher than the previous methods.

Crystal structure of an (R)-selective ω-transaminase from Aspergillus terreus

Chiral amines are important building blocks for the synthesis of pharmaceutical products, fine chemicals, and agrochemicals. ω-Transaminases are able to directly synthesize enantiopure chiral amines by catalysing the transfer of an amino group from a primary amino donor to a carbonyl acceptor with pyridoxal 5′-phosphate (PLP) as cofactor. In nature, (S)-selective amine transaminases are more abundant than the (R)-selective enzymes, and therefore more information concerning their structures is available. Here, we present the crystal structure of an (R)-ω-transaminase from Aspergillus terreus determined by X-ray crystallography at a resolution of 1.6 Å. The structure of the protein is a homodimer that displays the typical class IV fold of PLP-dependent aminotransferases. The PLP-cofactor observed in the structure is present in two states (i) covalently bound to the active site lysine (the internal aldimine form) and (ii) as substrate/product adduct (the external aldimine form) and free lysine. Docking studies revealed that (R)-transaminases follow a dual binding mode, in which the large binding pocket can harbour the bulky substituent of the amine or ketone substrate and the α-carboxylate of pyruvate or amino acids, and the small binding pocket accommodates the smaller substituent.

ω-Transaminase from Ochrobactrum anthropi is devoid of substrate and product inhibitions

ω-Transaminases display complicated inhibitions by ketone products and both enantiomers of amine substrates. Here, we report the first example of ω-transaminase devoid of such inhibitions. Owing to the lack of enzyme inhibitions, the ω-transaminase from Ochrobactrum anthropi enabled efficient kinetic resolution of α-methylbenzylamine (500 mM) even without product removal.

Features and technical applications of ω-transaminases

Chiral amines in enantiopure forms are important chemical building blocks, which are most well recognized in the pharmaceutical industries for imparting desirable biological activity to chemical entities. A number of synthetic strategies to produce chiral amines via biocatalytic as well as chemical transformation have been developed. Recently, ω-transaminase (ω-TA) has attracted growing attention as a promising catalyst which provides an environment-friendly access to production of chiral amines with exquisite stereoselectivity and excellent catalytic turnover. To obtain enantiopure amines using ω-TAs, either kinetic resolution of racemic amines or asymmetric amination of achiral ketones is employed. The latter is usually preferred because of twofold higher yield and no requirement of conversion of a ketone product back to racemic amine. However, the choice of a production process depends on several factors such as reaction equilibrium, substrate reactivity, enzyme inhibition, and commercial availability of substrates. This review summarizes the biochemical features of ω-TA, including reaction chemistry, substrate specificity, and active site structure, and then introduces recent advances in expanding the scope of ω-TA reaction by protein engineering and public database searching. We also address crucial factors to be considered for the development of efficient ω-TA processes.